Streaming Research Articles

‘Alexa, play metal’: exploring music selection and personal information management via voice assistants

Introduction. Music streaming services have changed how music is played and perceived, but also how it is managed by individuals. Voice interfaces to such services are becoming increasingly com-mon, for example through voice assistants on mobile and smart devices, and have the poten-tial to further change personal music management by introducing new beneficial features and new challenges. Method. To explore the implications of voice assistants for personal music listening and management we surveyed 248 participants online and in a lab setting to investigate (a) in which situa-tions people use voice assistants to play music, (b) how the situations compare to established activities common during non-voice assistant music listening, and (c) what kinds of com-mands they use. Analysis. We categorised 653 situations of voice assistant use, which reflect differences to non-voice assistant music listening, and established 11 command types, which mostly reflect finding or refinding activities but also indicate keeping and organisation activities. Results. Voice assistants have some benefits for music listening and personal music management, but also a notable lack of support for traditional personal information management activities, like browsing, that are common when managing music. Conclusion. Having characterised the use of voice assistants to play music, we consider their role in per-sonal music management and make suggestions for improved design and future research.

An Effective Investigation for Quality of Service Enhancement of Content Delivery Network for HTTP Live Streaming Using H.265

In the contemporary era, the prevailing trend among individuals is the widespread utilization of streaming technology to indulge in audio or video content emanating from a server. This innovative approach negates the necessity for downloading the content beforehand, allowing users to seamlessly revel in the material through the streaming mechanism. However, this cutting-edge technology mandates a substantial bandwidth to uphold its Quality of Service (QoS) at an optimal level. Challenges may arise, such as packet loss, attributed to the restricted bandwidth provided by the network service provider, thereby compromising the delivered content’s quality. To address this issue, one viable solution is the integration of CDN (Content Delivery Network), a technology proven to enhance the quality of content delivered through streaming services. This research endeavors to elevate the quality of live video streaming by leveraging CDN. The HTTP Live Streaming (HLS) format for content streaming, the study empirically demonstrates that CDN significantly improves the Quality of Service. As a result, the proposed method Content Delivery Network (CDN) using H.265 plays vital role in live video streaming. The result shows that live video streaming with CDN outperforms without CDN. Specifically, the live video streaming experience with CDN showcases a remarkable throughput average of 5899.7 kbps, coupled with a minimal packet loss ratio average of 0.05%. This stands in stark contrast to the version without CDN, which exhibits a comparatively diminished throughput average of 5287.3 kbps and a higher packet loss ratio average of 0.22%. These empirical findings strongly emphasize the effectiveness of CDN in elevating the Quality of Service for live video streaming. The tangible enhancements in throughput and the reduction of packet loss achieved through CDN implementationcontribute significantly to an enriched user experience. The evidence supports the notion that integrating CDN technology not only optimizes the technical performance of live video streaming but also plays a pivotal role in enhancing the overall satisfaction and engagement of users with the content delivery system.

Meta-Transcriptomic Analysis Reveals Novel RNA Viruses in Polychaetes Perinereis.

Perinereis species are essential benthonic animals in coastal ecosystems and have significant roles as live feed in aquaculture, owing to their high-protein and low-fat nutritional profile. Despite their ecological importance, the viral communities associated with these organisms need to be better understood. In this study, we generated 2.6 × 108 reads using meta-transcriptomic sequencing and de novo assembled 5.3 × 103 virus-associated contigs. We identified 12 novel RNA viruses from two species, Perinereis aibuhitensis and P. wilsoni, which were classified into four major viral groups: Picobirnaviridae, Marnaviridae, unclassified Picornavirales, and unclassified Bunyavirales. Our findings revealed the hidden diversity of viruses and genome structures in Perinereis, enriching the RNA virosphere and expanding the host range of Picobirnaviridae, Marnaviridae, and Bunyavirales. This study also highlighted the potential biosecurity risk of the novel viruses carried by Perinereis to aquaculture.

A music recommender system based on compact convolutional transformers

In recent years, music streaming services have garnered a surge in popularity. Maintaining a continuous flow of music that aligns with user preferences, commonly known as the continuity problem, has become a significant issue in this domain. To address this challenge, developing Music Recommender Systems (MRSs) that can automatically search through vast music libraries and suggest appropriate songs to listeners is crucial. To this end, this paper proposes a Compact Convolutional Transformer (CCT) model for improving the feature selection process and thus addressing the continuity problem based on music genres. The model extracts latent features from Mel-spectrograms generated from raw audio songs. Then, the cosine similarity measure determines the similarity between feature maps to recommend the most relevant songs. Several methodologies, including two state-of-the-art CRNN models, are used to benchmark the model’s performance. The experimental results demonstrate that the proposed model significantly outperforms the current state-of-the-art models in terms of precision, recall, F1 score, and overall accuracy while having significantly fewer parameters.

AI Assistant for Visually Impaired

This paper presents an advanced assistive technol- ogy system aimed at improving accessibility and independence for visually impaired individuals. Utilizing artificial intelligence (AI) and computer vision techniques, the system provides real- time auditory feedback to users about their surroundings. The core components of the system include image captioning, face recognition, and depth estimation, all integrated to offer a comprehensive understanding of the environment. The system captures live video feed through a webcam, processes the images using pre-trained models like CLIPSeg for image segmentation and DPT for depth estimation, and generates textual descriptions of detected objects and their spatial distances. These descriptions are translated from English to Kannada using Google’s transla- tion services and converted into speech with the gTTS library, ensuring accessibility for Kannada-speaking users. Additionally, the system employs face recognition to identify known individuals in the vicinity, providing personalized auditory notifications. The combination of these technologies enables the system to offer context-aware assistance, helping visually impaired users to navigate and interact with their surroundings more effectively. Experimental results demonstrate the system’s capability to deliver accurate, real-time feedback, highlighting its potential to significantly enhance the quality of life for visually impaired individuals.

Feeding protocol with live feed and inert diet to determine the ideal age/size for weaning mullet Mugil liza (Valenciennes, 1836).

The Lebranche mullet Mugil liza is a marine fish of great importance for artisanal and industrial fishing, as well as aquaculture. The use of live feeds during the larviculture phase of marine fish is a significant component of production costs. The present study evaluated the effects of the feeding transition on different larval stages of M. liza, from the combined supply of live feed (Brachionus rotundiformis + Artemia franciscana) and live + inert feed (Artemia franciscana + inert diet) until the weaning phase to only the inert diet. A total of 3240 M. liza larvae (weight 0.0133 ± 0.0062 g and length 0.793 ± 0.160 cm) were distributed among the 12 experimental units (n = 270), resulting in four groups with three replicates each. Treatment groups consisted of feed transition with A. franciscana (enriched metanauplii) to commercial inert feed starting weaning at four different larval ages: 28, 31, 34, and 37 days post hatching. Zootechnical performance indexes and intestinal histomorphometry were evaluated. Mortality, condition factor, and length variation coefficient did not show significant differences between treatments. Final weight, final length, weight gain, and length gain were significantly greater in larvae that started weaning at 31, 34, and 37 days post hatching. Weight coefficient of variation was significantly higher in larvae that started weaning at 28 days (67.51 ± 11.70) compared to 37 days (34.40 ± 7.30). In intestinal histology, villi height (180.3 ± 4.4) was significantly higher in larvae that started weaning at 37 days post hatching. Considering the evidence found in the present study, it is recommended to start weaning M. liza on the 31st day post-hatching, using a 2-day co-feeding protocol (31st and 32nd days). From the 33rd day after hatching, M. liza larvae can receive only commercial feed.

Musicotherapy mobile applications: what level of evidence and potential role in psychiatric care? A systematic review.

In our times of smartphone ubiquity, mobile applications are an inescapable daily life tool, including in health care. Music therapy has already proven its worth, notably in mental health. Hence, we were interested in the mobile app format for this type of therapy, its level of evidence, how to use it in daily psychiatric care and the leads for future research and innovation. This study carries out a systematic review of scientific literature of this topic on two search engines, PubMed and PubPsych, using these key-words: [(web-application) OR (web-app) OR (smartphone) OR (apps) OR (app)) AND ((music) OR (music therapy) OR (melody)]. Out of a total of 282 studies found by keyword, 31 are included in this review. Several outcomes emerge. These studies relate to existing applications like Music Care, Calm or Unwind, on application prototypes or a potential use of music streaming applications on health care. They involve many different populations and clinical situations, including in hospital environments, for patients with chronic illnesses, different age ranges or for the general population. These musical interventions show a significant effect mainly for anxious symptoms, but also for depression, sleep disorders, pain and other psychiatric or psycho-somatic syndromes. These applications have no significant adverse effects. This review shows that music therapy apps have several potentials for improving mental health care. It could assist psychiatric usual care and could potentially lower medication intake. Nevertheless, the studies on the topic are limited and recent but they open prospects for future research.

Telehealth With Comprehensive Live-Fed Real-World Data as a Patient Care Platform for Lung Cancer: Implementation and Evaluation Study.

Telehealth has emerged as a popular channel for providing outpatient services in many countries. However, the majority of telehealth systems focus on operational functions and offer only a sectional patient journey at most. Experiences with incorporating longitudinal real-world medical record data into telehealth are valuable but have not been widely shared. The feasibility and usability of such a telehealth platform, with comprehensive, real-world data via a live feed, for cancer patient care are yet to be studied. The primary purpose of this study is to understand the feasibility and usability of cancer patient care using a telehealth platform with longitudinal, real-world data via a live feed as a supplement to hospital electronic medical record systems specifically from physician's perspective. A telehealth platform was constructed and launched for both physicians and patients. Real-world data were collected and curated using a comprehensive data model. Physician activities on the platform were recorded as system logs and analyzed. In February 2023, a survey was conducted among the platform's registered physicians to assess the specific areas of patient care and to quantify their before and after experiences, including the number of patients managed, time spent, dropout rate, visit rate, and follow-up data. Descriptive and inferential statistical analyses were performed on the data sets. Over a period of 15 months, 16,035 unique users (13,888 patients, 1539 friends and family members, and 174 physician groups with 608 individuals) registered on the platform. More than 382,000 messages including text, reminders, and pictures were generated by physicians when communicating with patients. The survey was completed by 78 group leaders (45% of the 174 physician groups). Of the participants, 84% (65.6/78; SD 8.7) reported a positive experience, with efficient communication, remote supervision, quicker response to questions, adverse event prevention, more complete follow-up data, patient risk reduction, cross-organization collaboration, and a reduction in in-person visits. The majority of the participants (59/78, 76% to 76/78, 97.4%) estimated improvements in time spent, number of patients managed, the drop-off rate, and access to medical history, with the average ranging from 57% to 105%. When compared with prior platforms, responses from physicians indicated better experiences in terms of time spent, the drop-off rate, and medical history, while the number of patients managed did not significantly change. This study suggests that a telehealth platform, equipped with comprehensive, real-world data via a live feed, is feasible and effective for cancer patient care. It enhances inpatient management by improving time efficiencies, reducing drop-off rates, and providing easy access to medical history. Moreover, it fosters a positive experience in physician-patient interactions.

Pengaruh Daya Tarik Iklan, Citra Merek, dan Persepsi Harga Terhadap Minat Beli Layanan Netflix Covid-19

The Covid-19 pandemic, which began in 2020, has altered societal behavior patterns, including an increased reliance on online streaming services such as Netflix. This article analyzes the pandemic's impact on Netflix's services and the factors influencing post-pandemic user purchase intent. Through data and news quotations, this article highlights the significant growth of new Netflix users during the pandemic and the company's response to increased demand. Additionally, previous research on advertising appeal, brand image, and price perception is examined to understand how these factors affect user purchase intent. The research findings indicate that purchase decisions significantly influence user purchase intent for Netflix services. This finding is consistent with previous studies emphasizing the crucial role of advertising appeal in influencing purchase intent. Furthermore, a positive brand image has been proven to increase user purchase intent. However, in the context of price perception, no significant impact on purchase intent was found, underscoring that price does not significantly affect online customer purchase intent. In conclusion, to enhance user purchase intent and decision-making, it is important to consider advertising appeal and brand image aspects in Netflix's marketing strategy.

A novel similarity measure SF-IPF for CBKNN with implicit feedback data

PurposeThe increasing popularity of music streaming services also increases the need to customize the services for each user to attract and retain customers. Most of the music streaming services will not have explicit ratings for songs; they will have only implicit feedback data, i.e user listening history. For efficient music recommendation, the preferences of the users have to be infered, which is a challenging task.Design/methodology/approachPreferences of the users can be identified from the users' listening history. In this paper, a hybrid music recommendation system is proposed that infers features from user's implicit feedback and uses the hybrid of content-based and collaborative filtering method to recommend songs. A Content Boosted K-Nearest Neighbours (CBKNN) filtering technique was proposed, which used the users' listening history, popularity of songs, song features, and songs of similar interested users for recommending songs. The song features are taken as content features. Song Frequency–Inverse Popularity Frequency (SF-IPF) metric is proposed to find the similarity among the neighbours in collaborative filtering. Million Song Dataset and Echo Nest Taste Profile Subset are used as data sets.FindingsThe proposed CBKNN technique with SF-IPF similarity measure to identify similar interest neighbours performs better than other machine learning techniques like linear regression, decision trees, random forest, support vector machines, XGboost and Adaboost. The performance of proposed SF-IPF was tested with other similarity metrics like Pearson and Cosine similarity measures, in which SF-IPF results in better performance.Originality/valueThis method was devised to infer the user preferences from the implicit feedback data and it is converted as rating preferences. The importance of adding content features with collaborative information is analysed in hybrid filtering. A new similarity metric SF-IPF is formulated to identify the similarity between the users in collaborative filtering.

Can the Culture Density of the Marine Copepod Pseudodiaptomus nihonkaiensis be Improved by Installing an Artificial Substrate?

The understanding of the increasing population density of copepods in culture tanks contributes to establish their stable cultures at high productions for aquaculture industry, which are preferred live feeds for fish larvae. In the present study, the semi-benthic copepod Pseudodiaptomus nihonkaiensis were used as target species. This genus is often found from brackish water and its tolerance to a wide range of salinity and water quality has attracted attention as a potential commercial live feed for aquaculture. Population growth and egg production in the semi-benthic copepod P. nihonkaiensis are investigated. Copepods were cultured in tanks without mesh, with mesh lining tank walls, and with 2, 4 or 8 mesh partitions in each tank to identify the effect of substratum surface area on copepod population density. Linear regression revealed peaks in nauplius, copepodite, adult and total densities, and the cumulative number of eggs for all sampling events to correlate positively with substratum surface area (p<0.01). Greater substratum area within a culture tank may improve egg production by increasing habitat for ovigerous females. The simple installation of inexpensive artificial substrata in existing copepod culture tanks might improve the feasibility of using copepods as a live food in commercial-scale aquaculture.

Investigating Factors Influencing Consumer Intention to Use Online Streaming Services

This paper investigates factors influencing consumer intention to use online streaming services from the technology acceptance perspective based on the extended Technology Acceptance Model with additional variables – perceived enjoyment and incorporation with human and social constructs from Theory Reasoned Action. The consumer intention to use online streaming services remains unclear due to the gap between expectations of online streaming service providers and the high unsubscribe rate. This study deployed an online questionnaire to collect data from 250 Facebook users. Thus, the data collected for this study were from consumers not using online streaming services in Malaysia to understand the factors that could trigger their intention to use. The data collected were analysed using SPSS version 26 and PLS-SEM version 3.0. The role of self-efficacy as a moderator was examined to better understand consumer behaviour in online streaming services. The result revealed that subjective norms and perceived enjoyment have significantly impacted consumer intention to use online streaming services. Regarding the moderating effect of self-efficacy on the relationship between perceived ease of use and perceived usefulness, the outcome evidenced that self-efficacy plays a moderator role for both constructs. This paper attempts to fill the gap by extending the extant literature on consumer intention to use online streaming services by assessing the direct and moderating effects. Furthermore, the outcome of this study also provides valuable practical contributions for online streaming service providers by improving their understanding of consumer behaviour on the intention to use online streaming services.

An Enhanced Lung Cancer Identification and Classification Based on Advanced Deep Learning and Convolutional Neural Network

In this research, a fast, accurate, and stable system of lung cancer detection based on novel deep learning techniques is proposed. Lung cancer continues to be one of the most monumental global health concerns, which is why there is an urgent need for low-cost and non-invasive screening. Though the diagnostic methods that are most commonly in use include CTscan, X-ray etc. The interpretation by the human eye varies and errors are bound to occur. In response to this challenge, we outline a more automated approach that is based on deep learning models and can be used to classify lung pictures with high levels of accuracy. This research makes use of a large data set of lung scans categorised as normal, malignant, and benign. The first look what the data had in store threw up some correlation with picture size and what seemed to be category differences. Realizing that live feed requires constant input, each picture underwent grayscale conversion and dimensionality reduction. In order to effectively deal with the unbalanced nature of the dataset that was discovered in the study, the Synthetic Minority Oversampling Technique (SMOTE) was applied as a technique. In this presentation, three new designs were introduced: Model I, Model 2, and Model 3. Additionally, one architecture was developed with the purpose of merging the predictions of all three models. Furthermore, out of all the models created, the best model emerged as model 1 with approximately an accuracy of 84%. 7%. But the ensemble strategy which was intended to make the best of each of the models, produced an astounding 82. 5% accuracy. The specific advantages and misclassification behaviors of Model 2 and 3, although less accurate than Model 1 but are currently under evaluation for future Model ensemble improvements. The technique developed using deep learning addresses the challenges at a faster, efficient, and contactless approach to lung cancer analysis. The fact that it is capable of operating in tandem with others diagnostic instruments may help reduce diagnostic errors and enhance patient care. We have addressed this issue so that the various practitioners would be able to read this paper and we can go to the next generation of diagnostic technologies.

A Study of Dance Performance Producers’ Experiences with Online Streaming

A Study of Dance Performance Producers’ Experiences with Online Streaming

Advanced Tactical Helmet for Military Use

Abstract: Advanced features on a tactical helmet designed for military use. Soldiers in today's military operations must have improved situational awareness, strong communication skills, and superior protection when fighting. A new generation of tactical helmets with enhanced features is required because the standard helmets now in use do not adequately fulfil these criteria. To improve army performance and survivability The helmet has several extra features in addition to its extensive ESP32 CAM for real-time data visualization, communication systems for seamless inter-squad communication, and improved ballistic protection materials. Among these characteristics include the incorporation of a helmet camera's First-Person-View (FPV) live video feed into a base station, along with the base station's face detection capabilities for enhanced identification. SolidWorks was used in the design process to produce a unique 3D-printed helmet, while ESP32 and ESP8266 were used to power a custom mainboard that effectively controlled the helmet's functions. this creative solution aims to significantly improve military operations, increase survivability, and ensure the safety of soldiers on the battlefield.

A Comparative Study on Eid Advertisement Video through Corporate YouTube Channels and Audience Engagement in Malaysia

This study explores the trend of Eid-related video advertisements in Malaysia on online streaming platforms like YouTube, as focusing on major corporate channels such as Petronas, TNB, Malaysia Airlines, and Telekom Malaysia. Thus, the aim of the study is to explore the trend of Eid advertisements and Malaysian audience engagement through corporate video on YouTube Channel. Notable differences emerged in how each company portrayed these values, showcasing unique approaches to brand representation. Despite the commonality in values, the varied portrayal methods indicated distinct brand identities for each organisation. The analysis was conducted using content analysis through viewing the Eid advertising video which emphasised the importance of crafting a brand image within the Eid-themed video content to resonate and be memorable among viewers. Findings shows that while companies align on shared values for Eid advertisements, the way these values are communicated plays a crucial role in shaping the brand's image and audience engagement. Consistent and respectful representation of shared values building trust towards the audiences. Meanwhile, broadcasters must ensure that the advertisements they air are culturally sensitive and align with the values of the audience.

Strategic Agility and Performance of Pay Television Industry in Kenya.

The Pay TV market in Kenya operates in a highly competitive business environment, which in turn calls for aggressiveness and more efficient ways of keeping the business afloat. Advancement in technology also comes with several options for Pay TV customers such as online streaming which poses more threat to the market. This research seeks to assess the influence of strategic agility on the performance of the Kenyan Pay TV industry using Multichoice Kenya Limited as the case study. The objectives of this study were to establish the influence of leadership agility, determine the influence cultural agility, assess the influence of business agility, and to determine the influence of career agility on organizational performance in the Kenyan Pay TV industry. The study is of great significance to the government of Kenya since the improved performance of the Pay TV companies can generate more revenue for the government in form of taxes and license fees. New and existing Pay TV companies may also benefit from this study by employing agile strategies for competitive advantage as well as getting more information on how to handle uncertain situations in the business environment. Additionally, academicians who may want to research more on strategic agility may benefit by accessing more information from this study. The concept of strategic agility has not been sufficiently researched especially on the variables such as leadership agility, cultural agility, business agility, career agility and how they influence organizational performance. This research was anchored on four theories namely; The Great Man Theory, Theory of Change, Theory of Constraints, and the Broaden and Build Theory. The reviewed literature on these theories indicates that there is a positive influence of strategic agility on organizational performance. This is a cross-sectional study which involves 60 employees with managerial roles. Descriptive design was used in this study adopting qualitative and quantitative methods. Data collection was done through closed and open-ended questionnaires, keeping a register of questionnaire distribution and feedback collection. A pilot study was carried out to determine the accuracy, clarity and relevance of the study questionnaire. Data analysis was carried using SPSS (V29) and multiple regression analysis. The study found that leadership agility, cultural agility business agility and career agility all have a significant effect on the performance of Pay TV firms in Kenya. The top leadership of firms in Pay TV industry should establish cross-cultural collaboration initiatives to encourage knowledge-sharing and teamwork among employees from different cultural backgrounds, foster a culture that encourages and rewards agile leadership behaviors, such as risk-taking and experimentation and encourage leaders to seek mentorship and coaching to enhance their agility capabilities, should invest in technology and infrastructure that support flexibility and adaptability in responding to market changes and also develop cross-functional teams that can quickly adapt to changing business requirements and address emerging challenges, implement career development plans and pathways that align with the organization's strategic objectives and employees' career aspiration and encourage a growth mindset among employees.

Head-locked, world-locked, or conformal diminished-reality? An examination of different AR solutions for pedestrian safety in occluded scenarios

Many collisions between pedestrians and cars are caused by poor visibility, such as occlusion by a parked vehicle. Augmented reality (AR) could help to prevent this problem, but it is unknown to what extent the augmented information needs to be embedded into the world. In this virtual reality experiment with a head-mounted display (HMD), 28 participants were exposed to AR designs, in a scenario where a vehicle approached from behind a parked vehicle. The experimental conditions included a head-locked live video feed of the occluded region, meaning it was fixed in a specific location within the view of the HMD (VideoHead), a world-locked video feed displayed across the street (VideoStreet), and two conformal diminished reality designs: a see-through display on the occluding vehicle (VideoSeeThrough) and a solution where the occluding vehicle has been made semi-transparent (TransparentVehicle). A Baseline condition without augmented information served as a reference. Additionally, the VideoHead and VideoStreet conditions were each tested with and without the addition of a guiding arrow indicating the location of the approaching vehicle. Participants performed 42 trials, 6 per condition, during which they had to hold a key when they felt safe to cross. The keypress percentages and responses from additional questionnaires showed that the diminished-reality TransparentVehicle and VideoSeeThrough designs came out most favourably, while the VideoHead solution caused some discomfort and dissatisfaction. An analysis of head yaw angle showed that VideoHead and VideoStreet caused divided attention between the screen and the approaching vehicle. The use of guiding arrows did not contribute demonstrable added value. AR designs with a high level of local embeddedness are beneficial for addressing occlusion problems when crossing. However, the head-locked solutions should not be immediately dismissed because, according to the literature, such solutions can serve tasks where a salient warning or instruction is beneficial.

Mirroring the inequalities of mainstream music platforms: popularity, revenue, and monetization strategies on Bandcamp

ABSTRACT In the era of digital music streaming, understanding the monetization and popularity dynamics of online audio distribution platforms is crucial for both researchers and music industry professionals. While much of the existing research has focused on mainstream platforms such as Spotify and Apple Music, we study Bandcamp, an alternative marketplace that, among other things, empowers independent artists to upload and sell their music. Leveraging a rich dataset of one million Bandcamp sales, we investigate the distribution of popularity and revenues among artists on the platform. Our analysis reveals a substantial level of inequality, with a small core of musicians concentrating most of the purchases and revenues. Surprisingly, our results also indicate that many artists adopt a monetization strategy that involves devaluing their products, potentially leading to a cherry-picking of songs by consumers. These findings shed light on the challenges faced by alternative music distribution services and emphasize the need for further exploration of a fairer and more sustainable business model for independent artists.

The Effect of Premium Service Music Streaming Towards Consumer Satisfaction of Z Generation in Jakarta

The development of the internet and technology affects many aspects of life, such as the need to listen to music. To fulfill this need, new technology presents music streaming to make it easier for people to listen to music. Music streaming provides premium services to give users advantages when streaming music. The availability of premium service is expected to increase consumers’ satisfaction. This research aimed to identify premium service's effect on consumer satisfaction. This research used a quantitative method and a descriptive approach. This research sample was 100 Gen Z people in Jakarta, and music streaming was used. The data will be analyzed by using SPSS. The findings of this research showed the effect of premium service music streaming on consumer satisfaction of the Z generation with t value ≥ t table, and the result was 3.414 ≥ 1.664.