Speech Mode Research Articles

Quantifying the speech-gesture relation with massive multimodal datasets: Informativity in time expressions.

The development of large-scale corpora has led to a quantum leap in our understanding of speech in recent years. By contrast, the analysis of massive datasets has so far had a limited impact on the study of gesture and other visual communicative behaviors. We utilized the UCLA-Red Hen Lab multi-billion-word repository of video recordings, all of them showing communicative behavior that was not elicited in a lab, to quantify speech-gesture co-occurrence frequency for a subset of linguistic expressions in American English. First, we objectively establish a systematic relationship in the high degree of co-occurrence between gesture and speech in our subset of expressions, which consists of temporal phrases. Second, we show that there is a systematic alignment between the informativity of co-speech gestures and that of the verbal expressions with which they co-occur. By exposing deep, systematic relations between the modalities of gesture and speech, our results pave the way for the data-driven integration of multimodal behavior into our understanding of human communication.

Vowel duration measurement in school-age children with cochlear implant

ObjectivesNormal hearing system is an essential factor for accurate production of speech segments. It seems that cochlear implant prosthesis helps children with hearing impairment to speak more accurately than before receiving prosthesis. The current research aimed to compare the vowel duration in school-aged children with cochlear implants and that in children with normal hearing. Additionally, the performance of girls and boys in two groups were investigated. MethodsA cross-sectional and descriptive-analytical study was carried out to compare the vowel duration in 9- to 12-year-old children with cochlear implant and those with normal hearing. Participants were 52 children who were matched by age and sex. We asked the children to read the target words with each word including one vowel and then participants’ voice samples were recorded. Then, vowel duration was measured using Praat software. Finally, the vowel duration was compared between the two groups running independent sample t-test. The level of significance was (P < 0.05). ResultsThere was no statistically significant difference observed between the two groups in the mean values of the vowel duration for the six Persian vowels (P > 0.05). Also, no significant difference was found between boys and girls in the mean value of the vowel duration between the two groups (P > 0.05). ConclusionPersian vowels in school-aged children with cochlear implant and with typical hearing are produced with similar durations. This finding is probably related to the increased duration of using prosthesis in this age range and speech mode used to measure vowel duration in the present study.

EXPRESSIVE SPEECH ACTS IN THE STATUSES OF THE FACEBOOK USERS

This research is conducted based on two purposes; they are to identify the types of expressive speech act found in the statuses of the Facebook users, and to explain the modes of expressive utterance used in the statuses. Therefore, the data source is the social network that is Facebook and the data are the statuses of the Facebook users. The data are collected by using observational method, followed by non-participant observational technique and taking-note technique. The data analysis is based on pragmatic identity method proposed by Sudaryanto (2015) which is also supported by the theory of the types of expressive speech act by Ronan (2015), and theory about the modes of utterance from Alwi, et al (2000). The analysis result shows that there are fourteen types of expressive speech act in the statuses. They are the expression of agreement, disagreement, apology, gratitude, sorrow (sadness), exclamation (complaint), volition (hope), anger, disappointment, encouragement, satire, annoyance, pride, and congratulation. Meanwhile, the modes of expressive speech act that are used consist of declarative mode, interrogative mode, and exclamative mode. The importance of this research is to reveal or show that there is something else the Facebook users want to say behind their statuses. Sometimes, they do not really state what they mean in their statuses. They use indirect way and there lies the use of expressive speech act which can be stated in different way.

Development of a Digital Content-Free Speech Analysis Tool for the Measurement of Mental Health and Follow-Up for Mental Disorders: Protocol for a Case-Control Study

BackgroundThe prevalence of mental disorders worldwide is very high. The guideline-oriented care of patients depends on early diagnosis and regular and valid evaluation of their treatment to be able to quickly intervene should the patient’s mental health deteriorate. To ensure effective treatment, the level of experience of the physician or therapist is of importance, both in the initial diagnosis and in the treatment of mental illnesses. Nevertheless, experienced physicians and psychotherapists are not available in enough numbers everywhere, especially in rural areas or in less developed countries. Human speech can reveal a speaker’s mental state by altering its noncontent aspects (speech melody, intonations, speech rate, etc). This is noticeable in both the clinic and everyday life by having prior knowledge of the normal speech patterns of the affected person, and with enough time spent listening to the patient. However, this time and experience are often unavailable, leaving unused opportunities to capture linguistic, noncontent information. To improve the care of patients with mental disorders, we have developed a concept for assessing their most important mental parameters through a noncontent analysis of their active speech. Using speech analysis for the assessment and tracking of mental health patients opens up the possibility of remote, automatic, and ongoing evaluation when used with patients’ smartphones, as part of the current trends toward the increasing use of digital and mobile health tools.ObjectiveThe primary objective of this study is to evaluate measurements of participants' mental state by comparing the analysis of noncontent speech parameters to the results of several psychological questionnaires (Symptom Checklist-90 [SCL-90], the Patient Health Questionnaire [PHQ], and the Big 5 Test).MethodsIn this paper, we described a case-controlled study (with a case group and one control group). The participants will be recruited in an outpatient neuropsychiatric treatment center. Inclusion criteria are a neurological or psychiatric diagnosis made by a specialist, no terminal or life-threatening illnesses, and fluent use of the German language. Exclusion criteria include psychosis, dementia, speech or language disorders in neurological diseases, addiction history, a suicide attempt recently or in the last 12 months, or insufficient language skills. The measuring instrument will be the VoiceSense digital voice analysis tool, which enables the analysis of 200 specific speech parameters, and the assessment of findings using psychometric instruments and questionnaires (SCL-90, PHQ, Big 5 Test).ResultsThe study is ongoing as of September 2019, but we have enrolled 254 participants. There have been 161 measurements completed at timepoint 1, and a total of 62 participants have completed every psychological and speech analysis measurement.ConclusionsIt appears that the tone and modulation of speech are as important, if not more so, than the content, and should not be underestimated. This is particularly evident in the interpretation of the psychological findings thus far acquired. Therefore, the application of a software analysis tool could increase the accuracy of finding assessments and improve patient care.Trial RegistrationClinicalTrials.gov NCT03700008; https://clinicaltrials.gov/ct2/show/NCT03700008International Registered Report Identifier (IRRID)PRR1-10.2196/13852

Top-down modulation of neural envelope tracking: The interplay with behavioral, self-report and neural measures of listening effort.

When listening to natural speech, our brain activity tracks the slow amplitude modulations of speech, also called the speech envelope. Moreover, recent research has demonstrated that this neural envelope tracking can be affected by top-down processes. The present study was designed to examine if neural envelope tracking is modulated by the effort that a person expends during listening. Five measures were included to quantify listening effort: two behavioral measures based on a novel dual-task paradigm, a self-report effort measure and two neural measures related to phase synchronization and alpha power. Electroencephalography responses to sentences, presented at a wide range of subject-specific signal-to-noise ratios, were recorded in thirteen young, normal-hearing adults. A comparison of the five measures revealed different effects of listening effort as a function of speech understanding. Reaction times on the primary task and self-reported effort decreased with increasing speech understanding. In contrast, reaction times on the secondary task and alpha power showed a peak-shaped behavior with highest effort at intermediate speech understanding levels. With regard to neural envelope tracking, we found that the reaction times on the secondary task and self-reported effort explained a small part of the variability in theta-band envelope tracking. Speech understanding was found to strongly modulate neural envelope tracking. More specifically, our results demonstrated a robust increase in envelope tracking with increasing speech understanding. The present study provides new insights in the relations among different effort measures and highlights the potential of neural envelope tracking to objectively measure speech understanding in young, normal-hearing adults.

Multifunctional Rendering Swarm Robot

Multifunctional Rendering Swarm robot make a huge impact in this present busy world . This robot works perfectly as an surveillance robot as well as an personal assisting robot for household purposes and most of the work that carried on is swarm mechanism of the personal assisting robots. This have dual mechanism for moment such as mecanum wheel as well as Klann mechanism to the six legs to overcome the hard terrain landscapes in particular house surroundings , with and arm mechanism to pick and place of assigned objects. This robot can be controlled by voice as well as limited hand gestures to perform tasks which use text to speech and speech to text, Convolution Neural Networking (CNN) respectively . This robot have a 3600 night vision camera for surveillance at night times through OpenCV . This will be doing parallel jobs such as talking to you as an assistant , cleaning house , and many more . as the advancement in the world is not up-to the real time applications, this helps in interfacing future and present situations to get updated. As swarm robots, this will be updating its status to the fellow robots and assigning particular task to divide and do faster which depends on deep learning and artificial intelligence. All this can be acknowledged and examined by any nominee of the user who are at distant places in case of any emergency and respond as a speech modulation talk back , digital display available for commands display or any work been processed, time consuming smart work is been done through this robot. This is also equipped with the sanitizer for the people hygiene and safety. This robots can also be used in military, schools, software industries and many more industries.

IMPLICATES IN THE NOVEL PULANG WORKS OF LEILA SALIKHA CHUDORI USING A PRAGMATIC APPROACH

This study aims to describe (1) Types of Implications in the novel Pulang by Leila Salikha Chudori (2) Implications in the novel Pulang by Leila Salikha Chudori and (3) Mode of Speech in the novel Pulang by Leila Salikha Chudori. This research is descriptive research. This research is focused on issues related to the implications of the pragmatic approach. The purpose of this research is to describe the conventional implicatures and the conversational implicatures. The data in this study are in the form of sentences in utterances that contain implicatures. Obtaining data in this study by reading and note taking techniques. After the data is collected, the data is classified according to its type, form and mode. After the classification of the data is completed then analyzed to find out the sentences containing the implicature then the conclusion of the research results.

Fugitive Listening: Sounds from the Undercommons

This essay builds on various critiques of the relationship between the voice and autonomous individual subjectivity, briefly tracking the specific history through which the voice transformed into an ideal object representing the liberal subject of post-Enlightenment thought. This paper asks: what are we to make of those enfleshed voices that do not conform to the ideal voice of the self-possessed liberal subject? What are we to make of those voices that refuse the imperative of improvement that underpins social and economic contractualism? How might we attend to the sonicity of those voices that refuse to individuate, possess, and accumulate? And what fugitive modes of speech might be transmitted by such un-formed and un-organized voices? Against the idealized voice of liberalism, and the gendered and racialized exclusions that this voice implies, I propose a mode of fugitive listening that allows us to open our ears to the noisy voices and modes of speech that sound outside the locus of politics proper. Indebted to the Black radical tradition, fugitive listening attends to sonic practices that refuse the given grounds of representation. I argue that fugitive listening is a practice that can be situated in what Stefano Harney and Fred Moten call ‘the undercommons’. The essay concludes by turning to gossip, figuring this noisy modality of speech as central to undercommon spaces shaped by Black performance.

Aggressiveness of emojis before the court: a sociosemiotic interpretation

ABSTRACTEmojis, used evidentially as any language is used in communication, have posed new challenges for courts to adopt emojis as evidence beyond the traditional mode of speech and communication and to interpret them appropriately, especially their aggressive side of meaning. To meet these challenges, the present study, based on a comprehensive literature review, starts with case studies with aims to unravel the nature of emojis and develop a sociosemiotic approach to interpret emojis in the context of social media with a focus on the aggressiveness of emojis in social platforms and their consequences (social and legal ones). It is argued that the meaning of emojis could not simply depend on their grammar or general rules but lies in communication within discourse communities.

The Effects of Contextual Priming and Alaryngeal Speech Mode on Auditory-Perceptual Ratings of Listener Comfort

The effectiveness of postlaryngectomy communication methods (esophageal, tracheoesophageal, and electrolaryngeal speech) has been primarily evaluated using functional outcomes. This evaluation neglects the importance of listeners and their influence on communicative effectiveness. Listener comfort (LC), or the ease with which a listener interacts with alaryngeal speakers, may provide an important index of communicative effectiveness. The present study investigated the use of LC in the auditory-perceptual evaluation of alaryngeal speech modes, as well as evaluating the influence of contextual cues used to elicit ratings on listener judgments of all three alaryngeal modes. Thirty-three naïve listeners provided independent ratings of LC for 39 alaryngeal speech samples using a visual analogue scaling procedure. Each group of listeners rated alaryngeal speech in three imagined listening conditions (Telephone Conversation, Social Situation, and a non-specified Control Condition). To analyze LC ratings obtained, a 3×3 mixed factor analysis of variance was conducted. A significant interaction effect between alaryngeal speech mode and listening condition (P=0.04) was identified. Overall, pairwise comparisons of alaryngeal speech mode indicated that listeners were more comfortable when presented with tracheoesophageal speech samples compared to those of esophageal and electrolaryn geal speakers. Our data suggest that LC ratings are influenced by alaryngeal speech mode. Tracheoesophagea speech was perceived to have the most favorable LC ratings compared to the other alaryngeal speech modes in all listening conditions. Contextual cues (i.e., social condition and telephone condition) did not have an effect on LC ratings.

Hearing Aid Amplification Reduces Communication Effort of People With Hearing Impairment and Their Conversation Partners.

Objectives This study investigates the hypothesis that hearing aid amplification reduces effort within conversation for both hearing aid wearers and their communication partners. Levels of effort, in the form of speech production modifications, required to maintain successful spoken communication in a range of acoustic environments are compared to earlier reported results measured in unaided conversation conditions. Design Fifteen young adult normal-hearing participants and 15 older adult hearing-impaired participants were tested in pairs. Each pair consisted of one young normal-hearing participant and one older hearing-impaired participant. Hearing-impaired participants received directional hearing aid amplification, according to their audiogram, via a master hearing aid with gain provided according to the NAL-NL2 fitting formula. Pairs of participants were required to take part in naturalistic conversations through the use of a referential communication task. Each pair took part in five conversations, each of 5-min duration. During each conversation, participants were exposed to one of five different realistic acoustic environments presented through highly open headphones. The ordering of acoustic environments across experimental blocks was pseudorandomized. Resulting recordings of conversational speech were analyzed to determine the magnitude of speech modifications, in terms of vocal level and spectrum, produced by normal-hearing talkers as a function of both acoustic environment and the degree of high-frequency average hearing impairment of their conversation partner. Results The magnitude of spectral modifications of speech produced by normal-hearing talkers during conversations with aided hearing-impaired interlocutors was smaller than the speech modifications observed during conversations between the same pairs of participants in the absence of hearing aid amplification. Conclusions The provision of hearing aid amplification reduces the effort required to maintain communication in adverse conditions. This reduction in effort provides benefit to hearing-impaired individuals and also to the conversation partners of hearing-impaired individuals. By considering the impact of amplification on both sides of dyadic conversations, this approach contributes to an increased understanding of the likely impact of hearing impairment on everyday communication.

VEP Detection for Read, Extempore and Conversation Speech

ABSTRACT In this paper, we propose a novel approach for accurate detection of the vowel end points (VEPs) in any mode of speech. VEP is the instant at which the vowel ends in the speech signal. In this study, we have considered three broad modes of speech, namely; conversation, extempore, and read. The existing methods were explored the VEP detection for read mode of speech, and it may not be appropriate for the VEP detection in extempore and conversation modes. This is due to the acoustic characteristic of read mode is very different from the modes as mentioned earlier. To handle this problem, we proposed a two-stage method for accurately detecting the VEPs, irrespective of modes. At the first stage, vowel onset points (VOPs) are detected in a speech signal using our recent method based on continuous wavelet transform and phone boundary. VOP represents the start of the vowel in the speech signal. At the second stage, phone boundaries are detected using spectral transition measure approach, and then the closest succeeding phone boundary for each detected VOP is considered as detected VEP. Experiments involve TIMIT and Bengali speech corpora. Performance of the proposed VEP detection method is compared with two state-of-the-art signal processing methods. The significance of the proposed method is shown by automatically detecting vowel regions from the TIMIT and Bengali speech corpora. The evaluation results report that the performance of the proposed method is significantly better than the existing methods.

Multilingual and multimode phone recognition system for Indian languages

The aim of this paper is to develop a flexible framework capable of automatically recognizing phonetic units present in a speech utterance of any language spoken in any mode. In this study, we considered two modes of speech: conversation and read modes in four Indian languages, namely, Telugu, Kannada, Odia, and Bengali. The proposed approach consists of two stages: (i) Automatic speech mode classification (SMC) and (ii) Automatic phoneme recognition using mode-specific multilingual phone recognition system (MMPRS). The vocal tract and excitation source features are considered for classifying speech modes using feed forward neural networks (FFNNs). The vocal tract, excitation source, and tandem features are used in training deep neural network (DNN)-based multilingual phone recognition systems (MPRSs). The performance of the proposed approach is compared with baseline mode-dependent and mode-independent MPRSs. Experimental results show that the proposed approach which combines both SMC and MMPRS into a single system outperforms the baseline phone recognition systems.

Anatomoelectroclinical features of SEEG-confirmed pure insular-onset epilepsy

PurposeIn this study, we aimed to improve our knowledge of insular epilepsy by studying anatomoelectroclinical correlations in pure insular-onset epilepsy and characterizing differences between anterior and posterior insular-onset seizures. MethodsPatients in whom seizure-onset zone was confined to the insula and peri-insular sulcus were selected from 301 consecutive presurgical stereo-electroencephalography (EEG) recordings performed between years 2010 and 2017 in two epilepsy centers. Ictal-onset zone in stereo-EEG was delineated visually and quantitatively using epileptogenic index method. Seizure characteristics were reanalyzed, and anatomoelectroclinical correlations were assessed. Characteristics of posterior and anterior insular-onset seizures were compared. ResultsEleven insular cases were identified, five of them with an anterior insular seizure onset and six with a posterior one. Nonpainful somatosensory symptoms and autonomic symptoms were the most common symptoms (73% of patients) followed by speech-related symptoms (55%) and ipsilateral eye blinking (45%). Six patients had seizures restricted to somatosensory or viscerosensory symptoms. In all patients, seizures progressed to motor symptoms. Somatosensory symptoms did not differentiate anterior from posterior insular seizures. However, hyperkinetic signs, speech modifications, and viscerosensory symptoms were related to an anterior insular seizure-onset zone. Pain, asymmetric tonic, focal clonic, and tonic symptoms were more frequent in patients with a posterior insular seizure onset. ConclusionsSeizure semiology is heterogeneous in pure insular-onset epilepsy. Differences between the anterior and posterior insular seizures reflect the functional organization of the insula. Particularly, the different types of motor symptoms may help to distinguish anterior from posterior insular seizure onset.

Contumelious oratory: reflecting on rhetorical forms in the Trump administration

ABSTRACT The absence of Jews from President Donald Trump’s 2017 Holocaust Remembrance Day speech was not the first occasion Trump’s relationship to anti-Semitism was brought up by the popular press, but this paper argues it is one example of many in the emergence of a new mode of presidential speech in the United States that I term “contumelious oratory.” This paper analyzes several examples of the Trump’s administration’s rhetoric including tweets, press conferences, and public speeches. I read the Trump administration’s briefness, strategic absences, metaphors, and hyperbolic statements as salient features of the new, contumelious oratorical mode. It is important to identify how this communication departs from traditional presidential speech of previous United States presidents, classify the techniques used, and grasp clearly the potential damage this type of speech can do. The Trump teams’ contumelious oratory does not placate, it provokes.

Enhanced amplitude modulations contribute to the Lombard intelligibility benefit: Evidence from the Nijmegen Corpus of Lombard Speech.

Speakers adjust their voice when talking in noise, which is known as Lombard speech. These acoustic adjustments facilitate speech comprehension in noise relative to plain speech (i.e., speech produced in quiet). However, exactly which characteristics of Lombard speech drive this intelligibility benefit in noise remains unclear. This study assessed the contribution of enhanced amplitude modulations to the Lombard speech intelligibility benefit by demonstrating that (1) native speakers of Dutch in the Nijmegen Corpus of Lombard Speech produce more pronounced amplitude modulations in noise vs in quiet; (2) more enhanced amplitude modulations correlate positively with intelligibility in a speech-in-noise perception experiment; (3) transplanting the amplitude modulations from Lombard speech onto plain speech leads to an intelligibility improvement, suggesting that enhanced amplitude modulations in Lombard speech contribute towards intelligibility in noise. Results are discussed in light of recent neurobiological models of speech perception with reference to neural oscillators phase-locking to the amplitude modulations in speech, guiding the processing of speech.

Individual differences in human voice pitch are preserved from speech to screams, roars and pain cries.

Fundamental frequency (F0, perceived as voice pitch) predicts sex and age, hormonal status, mating success and a range of social traits, and thus functions as an important biosocial marker in modal speech. Yet, the role of F0 in human nonverbal vocalizations remains unclear, and given considerable variability in F0 across call types, it is not known whether F0 cues to vocalizer attributes are shared across speech and nonverbal vocalizations. Here, using a corpus of vocal sounds from 51 men and women, we examined whether individual differences in F0 are retained across neutral speech, valenced speech and nonverbal vocalizations (screams, roars and pain cries). Acoustic analyses revealed substantial variability in F0 across vocal types, with mean F0 increasing as much as 10-fold in screams compared to speech in the same individual. Despite these extreme pitch differences, sexual dimorphism was preserved within call types and, critically, inter-individual differences in F0 correlated across vocal types (r = 0.36–0.80) with stronger relationships between vocal types of the same valence (e.g. 38% of the variance in roar F0 was predicted by aggressive speech F0). Our results indicate that biologically and socially relevant indexical cues in the human voice are preserved in simulated valenced speech and vocalizations, including vocalizations characterized by extreme F0 modulation, suggesting that voice pitch may function as a reliable individual and biosocial marker across disparate communication contexts.

Two-Stage Fuzzy Fusion Based-Convolution Neural Network for Dynamic Emotion Recognition

The two-stage fuzzy fusion based-convolution neural network is proposed for dynamic emotion recognition by using both facial expression and speech modalities, which not only can extract discriminative emotion features which contain spatio-temporal information, but also can effectively fuse facial expression and speech modalities. Moreover, the proposal is able to handle situations where the contributions of each modality data to emotion recognition are very imbalanced. The local binary patterns coming from three orthogonal planes and spectrogram are considered first to extract low-level dynamic emotion, so that the spatio-temporal information of these modalities can be obtained. To reveal more discriminative features, two deep convolution neural networks are constructed to extract high-level emotion semantic features. Moreover, the two stage fuzzy fusion strategy is developed by integrating canonical correlation analysis and fuzzy broad learning system, so as to take into account the correlation and difference between different modal features, as well as handle the ambiguity of emotional state information. The experimental results obtained on benchmark databases show that the accuracies of the proposed method are higher than those of existing methods (such as the hybrid deep model, and the rule-based and machine learning method) on SAVEE, eNTERFACE&#x2019;05, and AFEW databases.

Specialized memory systems for learning spoken words.

Learning new words entails, inter alia, encoding of novel sound patterns and transferring those patterns from short-term to long-term memory. We report a series of 5 experiments that investigated whether the memory systems engaged in word learning are specialized for speech and whether utilization of these systems results in a benefit for word learning. Sine-wave synthesis (SWS) was applied to spoken nonwords, and listeners were or were not informed (through instruction and familiarization) that the SWS stimuli were derived from actual utterances. This allowed us to manipulate whether listeners would process sound sequences as speech or as nonspeech. In a sound-picture association learning task, listeners who processed the SWS stimuli as speech consistently learned faster and remembered more associations than listeners who processed the same stimuli as nonspeech. The advantage of listening in "speech mode" was stable over the course of 7 days. These results provide causal evidence that access to a specialized, phonological short-term memory system is important for word learning. More generally, this study supports the notion that subsystems of auditory short-term memory are specialized for processing different types of acoustic information. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A Novel Integrity Authentication Algorithm Based on Perceptual Speech Hash and Learned Dictionaries

Perceptual speech hash and robust watermarking have been widely investigated to solve the problems of authenticating speech integrity. The former generates a watermark and the latter embeds the watermark into the speech signal to implement speech integrity authentication. In this paper, we propose a perceptual speech hash algorithm and a robust watermarking algorithm for speech integrity authentication. To obtain perceptual speech hash values, we propose a gammatone filter model of the speech signal to extract sensitive auditory features (denoted by gammatone features). A random Gaussian matrix is used to reduce the dimensionality of the features of the gammatone to generate perceptual speech hash values. For the watermarking algorithm, we construct learned dictionaries to obtain the robust sparse feature of coefficients of the stationary wavelet transforms, and embed a watermark (perceptual speech hash values) into the sparse feature by patchwork and quantization index modulation. We illustrate the good imperceptibility of the authentication scheme in terms of the signal-to-noise ratio, objective difference grade, and subjective difference grade, and verify its robustness against common signal processing operations while maintaining imperceptibility. Moreover, our proposed method is sensitive to the malicious modification of the watermarked speech. Compared with state-of-the-art algorithms, the proposed algorithm can obtain better comprehensive performance in the detection and localization of tampering with the content of speech.