Segment Duration Research Articles

QoE optimization for HTTP adaptive streaming: Performance evaluation of MEC-assisted and client-based methods

Seamless streaming of high quality video under unstable network condition is a big challenge. HTTP adaptive streaming (HAS) provides a solution that adapts the video quality according to the network conditions. Traditionally, HAS algorithm runs at the client side while the clients are unaware of bottlenecks in the radio channel and competing clients. The traditional adaptation strategies do not explicitly coordinate between the clients, servers, and cellular networks. The lack of coordination has been shown to lead to suboptimal user experience. As a response, multi-access edge computing (MEC)-assisted adaptation techniques emerged to take advantage of computing and content storage capabilities in mobile networks. In this study, we investigate the performance of both MEC-assisted and client-side adaptation methods in a multi-client cellular environment. Evaluation and comparison are performed in terms of not only the video rate and dynamics of the playback buffer but also the fairness and bandwidth utilization. We conduct extensive experiments to evaluate the algorithms under varying client, server, dataset, and network settings. Results demonstrate that the MEC-assisted algorithms improve fairness and bandwidth utilization compared to the client-based algorithms for most settings. They also reveal that the buffer-based algorithms achieve significant quality of experience; however, these algorithms perform poorly compared with throughput-based algorithms in protecting the playback buffer under rapidly varying bandwidth fluctuations. In addition, we observe that the preparation of the representation sets affects the performance of the algorithms, as does the playback buffer size and segment duration. Finally, we provide suggestions based on the behaviors of the algorithms in a multi-client environment.

Abstract 12211: Water Hammer Shock Causing Rupture Of Vulnerable Cap Of Culprit Lesions In Acute Coronary Syndrome: An Angiographic And Machine Learning Analysis

Introduction: Acute coronary syndrome (ACS) is caused by rupture of coronary plaques. What triggers these ruptures? Hypothesis: In the field of hydraulics, in a setting of a tank and draining pipe, if the valve at the distal end of the pipe is open, the fluid flows normally. If the valve closes abruptly, the flow next to the valve stops. However the fluid from the tank continues to flow forward and can collide with the distal stationary fluid. This is called water hammer shock. Could the same event happen in coronary arteries? The contraction of the left ventricle (LV) is similar to the abrupt closure of a valve, stopping the myocardial capillary flow. Could the systolic LV contraction trigger water hammer shock? Methods: Angiograms with culprit lesions of ACS (recorded at 15 images/second or 0.06 second per image) were reviewed. The first image was of the artery completely filled with contrast. The subsequent images showed the blood in white color blood moving in over a background of black contrast. The normal flow was laminar. When there was retrograde on top of turbulent flow, this was evidence of a collision between antegrade and retrograde flow (or water hammer shock). The measurements by visual angiographic evaluation and by Machine Learning (ML) included (1) the duration and (2) size of coronary segment with turbulence. The ML program had 2 models (build on Python). Model 1 was built based on U-net and Densenet-121 for vessel segmentation. Model 2 was used for classification of flow. The model 2 was trained based on the convolutional neural network. Results: Angiograms of 20 ACS patients showed laminar flow (90%) in diastole. The flow became turbulent during systole with retrograde flow. The area of collision or water hammer shock showed diffuse coarse mixing of black (contrast) and white (blood). The presence of turbulence matched the location of 85% of ruptured plaques. The duration of turbulence lasted 80% of systole. Special protocols were used successfully to train AI to recognize the lesions, retrograde and turbulent flow. Conclusions: With the new angiographic technique, detailed images of water hammer shock matched the location of ruptured plaques in ACS patients. These results may help to understand the genesis and offer precise prevention and treatment for ACS

Tonal cues to prosodic structure in rate-dependent speech perception.

This study explores how listeners integrate tonal cues to prosodic structure with their perception of local speech rate and consequent interpretation of durational cues. In three experiments, we manipulate the pitch and duration of speech segments immediately preceding a target sound along a vowel duration continuum (cueing coda stop voicing), testing how listeners' categorization of vowel duration shifts based on temporal and tonal context. We find that listeners perceive the presence of a phrasal boundary tone on a lengthened syllable as signaling a slowdown in speech rate, shifting perception of vowel duration, with effects that are additive when crossed in a 2 × 2 (pitch × duration) design. However, an asymmetrical effect of pitch and duration is found in an explicit duration judgement task in which listeners judge how long a pre-target syllable sounds to them. In explicit rate judgement, only durational information is consequential, unlike the categorization task, suggesting that integration of tonal and durational prosodic cues in rate-dependent perception is limited to implicit processing of speech rate. Results are discussed in terms of linguistic information in rate-dependent speech processing, the integration of prosodic cues, and implicit and explicit rate processing tasks.

Native listeners rely on rhythmic cues when deciding on the nativeness of speech.

Foreign-accented speech typically deviates segmentally and suprasegmentally from native-accented speech. Two experiments were conducted to investigate the role of amplitude envelope (ENV), segment duration (DUR), and speech rate (SR) on Italian listeners' ability to identify native-accented Italian in utterances produced by Zurich German speakers. In experiment 1, listeners judged in a two-alternative forced-choice perception task which of the two stimuli in a trial they perceived as more native-like. Stimuli in each trial only varied in ENV and DUR, which were retrieved either from a native Italian speaker [first language (L1) donor] or from a German speaker of Italian [second language (L2) donor]. Results revealed that listeners make use of both DUR and ENV to identify the more native-like stimuli, but the effect of ENV was more subtle. In experiment 2, SR differences (resulting from native and non-native segment duration differences in experiment 1) were normalized for. It was found that this drastically reduced the effect of segment durations in terms of perceived nativeness; however, the ENV effect still remained. This was not the case in a control group of listeners without competence in Italian. Though effects were subtle, the study shows that ENV cues contribute to the percept of nativeness in L2 speech.

A COMPARATIVE STUDY OF 0.5 % BUPIVACAINE WITH FENTANYL VERSUS 0.75% ROPIVACAINE WITH FENTANYL IN EPIDURALANESTHESIA FOR ABDOMINAL HYSTERECTOMY

INTRODUCTION Abdominal hysterectomy (AH) is a quite common gynaecological surgical procedure and electively done under central neuraxial blockade. AH is performed for malignant as well as benign indications such as uterine leiomyoma, persistent vaginal bleeding, or pelvic organ prolapse. AIMS AND OBJECTIVES Compare the onset of motor and sensory block. Find out the duration of the sensory and motor blockade. Observe intraoperative hemodynamic changes and assess post-operative analgesia requirements in 24 hour. Duration of analgesia assessed by requirement of rst rescue analgesic. Observe any untoward incident during intraoperative and post-operative period and managed accordingly MATERIALS AND METHODS Study Area: Department of Anesthesiology & critical care, DARBHANGAMEDICALCOLLEGE AND HOSPITAL. Study Population: Adult patients (30- 65 years) undergoing elective abdominal hysterectomy with regional anaesthesia were included for this study. Study Period:January 2019 to March 2020 Sample Design: Subjects were divided into two groups (n=35) equal in numbers and they sampled as per computerized randomization chart. These patients were divided into two groups, group B (with epidural 0.5% bupivacaine and 100g fentanyl) and group R (with epidural 0.75% ropivavaine and 100g fentanyl). Study Design: Prospective, open, randomized, controlled study. RESULTS: In Our study showed that 3.38kg/m2 and 24.86 3.60 kg/m2in group B and R respectively. The duration of surgery was 100.86 9.35minutes and 98.86 8.32 minutes and the duration of stay, was4.86 0.81days and 4.60 0.914 days in group B and group R respectively. Now with comparison of both groups, time to onset of sensory block (uptoT6) has signicant variation. But the other parameters namely, time to onset of motor block, two segment regression or duration of sensory block, rescue analgesia timing and complete motor recovery time were comparable and not signicant statistically in both groups. SUMMARY & CONCLUSIONS To conclude that in the present study using 0.5% bupivacaine with fentanyl and 0.75% ropivacaine with fentanyl epidurally, ropivacaine produced an earlier onset but similar duration of sensory block. The onset, quality and duration of motor block werecomparable in both the groups. It is important that new local anaesthetics with lower cardiotoxic property are adopted to ensure that regional techniques using large amounts of local anaesthetics remain safe with minimal complications. The recovery prole of ropivacaine may be useful where prompt mobilization is require

Overlapped speech detection using phase features.

Simultaneous speech of multiple speakers is known as overlapped speech, which causes problems for speech recognition and speaker diarization systems. The present work uses previously less utilized signal phase information in the task of overlapped speech detection. In this context, Instantaneous Frequency Cosine Coefficient (IFCC) and Modified Group Delay Cepstral Coefficient (MGDCC) features are explored. IFCC captures the time-varying phase characteristics, while MGDCC represents the frequency-varying information of the phase spectrum. A Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM)-based classifier is used for the classification. The present work uses synthetically generated overlapped speech from the GRID corpus. The proposed method is benchmarked against three baseline approaches that use magnitude spectrum features. It is observed that the combination of IFCC and MGDCC features with CNN-LSTM classifier provides better performance than the baselines. The combination of phase features with magnitude-based MFCC feature provides the best performance, indicating the importance of complementary information. The present study also investigates the effect of segment duration, genders, and number of simultaneous speakers on the overlapped speech detection system. Finally, the proposed method is also evaluated on real overlapped data from the AMI corpus.

Acoustic cues to non-native-directed speech

Facing linguistic barriers to communication, talkers spontaneously adjust their speech, facilitating perception by their listener. These adjustments characteristically involve hyperarticulation, such as reduced speech rate, increased vowel dispersion, and increased segmental duration. Listener-based hyperarticulation could result from listener modeling, in which the talker monitors their listener’s comprehension. Hyperarticulation could also result from rich phonological representations, in which listener-based variation is directly represented. This study examined predictions of monitoring and representational accounts of listener-based hyperarticulation using a perception task. Participants completed a forced-choice identification task which tasked them with identifying the background of an interlocutor from recorded speech. That speech was originally produced to imagined and real and to native and non-native interlocutors. If listener-based variation originates with listener modeling, accuracy should be high and similar for each listener background. If that variation originates from rich representations, accuracy should be low, variable, and different across listener backgrounds. The results revealed poor accuracy, even for speech directed toward imagined non-natives, the most hyperarticulate speech. Participants’ choices were influenced most by speech rate, second by vowel dispersion, but not by vowel duration. We discuss the implications of these results for cognitive models of listener-based phonetic variation.

Paradigmatic Relations Interact During the Production of Complex Words: Evidence From Variable Plurals in Dutch.

A growing body of work in psycholinguistics suggests that morphological relations between word forms affect the processing of complex words. Previous studies have usually focused on a particular type of paradigmatic relation, for example the relation between paradigm members, or the relation between alternative forms filling a particular paradigm cell. However, potential interactions between different types of paradigmatic relations have remained relatively unexplored. This paper presents two corpus studies of variable plurals in Dutch to test hypotheses about potentially interacting paradigmatic effects. The first study shows that generalization across noun paradigms predicts the distribution of plural variants, and that this effect is diminished for paradigms in which the plural variants are more likely to have a strong representation in the mental lexicon. The second study demonstrates that the pronunciation of a target plural variant is affected by coactivation of the alternative variant, resulting in shorter segmental durations. This effect is dependent on the representational strength of the alternative plural variant. In sum, by exploring interactions between different types of paradigmatic relations, this paper provides evidence that storage of morphologically complex words may affect the role of generalization and coactivation during production.

A Literature Review of Neural Tracking to Speech Envelope from the View of Audiology

Despite the significant contribution of hearing assistive devices, medications, and surgery to restoring auditory periphery, a large number of people with hearing loss still struggle with understanding speech. This leads many studies on speech perception to move towards the central auditory functions by looking at associated brain activities using macroscopic recording tools such as electroencephalography (EEG). Up until a few years ago, however, limitation has been given to the brain scientists who attempted to investigate speech perception mechanisms using the EEG. In particular, short duration of speech segments has inevitably been used to elicit auditory evoked potential, even though they were too brief to be considered as speech. Today, however, advance in neural engineering and better understanding of neural mechanism have better facilitated brain scientists to perform studies with running stream of continuous speech and expand the scope of EEG studies to include comprehension of more realistic speech envelope. The purpose of this study is to review literatures on neural tracking to speech envelope to discuss it in Audiology perspective. This review article consists of seven subjects including introduction, neural tracking theories, neural tracking measure, signal processing & analysis, literature review on neural tracking associated with hearing loss, application of neural tracking to audiology, and conclusion. We noted that neural tracking has potential to be used in clinical sets to objectively evaluate speech comprehension for people with hearing loss in the future.

On the Impact of the Data Acquisition Protocol on ECG Biometric Identification.

Electrocardiographic (ECG) signals have been used for clinical purposes for a long time. Notwithstanding, they may also be used as the input for a biometric identification system. Several studies, as well as some prototypes, are already based on this principle. One of the methods already used for biometric identification relies on a measure of similarity based on the Kolmogorov Complexity, called the Normalized Relative Compression (NRC)—this approach evaluates the similarity between two ECG segments without the need to delineate the signal wave. This methodology is the basis of the present work. We have collected a dataset of ECG signals from twenty participants on two different sessions, making use of three different kits simultaneously—one of them using dry electrodes, placed on their fingers; the other two using wet sensors placed on their wrists and chests. The aim of this work was to study the influence of the ECG protocol collection, regarding the biometric identification system’s performance. Several variables in the data acquisition are not controllable, so some of them will be inspected to understand their influence in the system. Movement, data collection point, time interval between train and test datasets and ECG segment duration are examples of variables that may affect the system, and they are studied in this paper. Through this study, it was concluded that this biometric identification system needs at least 10 s of data to guarantee that the system learns the essential information. It was also observed that “off-the-person” data acquisition led to a better performance over time, when compared to “on-the-person” places.

Checkerboard speech vs interrupted speech: Effects of spectrotemporal segmentation on intelligibility.

The intelligibility of interrupted speech (interrupted over time) and checkerboard speech (interrupted over time-by-frequency), both of which retained a half of the original speech, was examined. The intelligibility of interrupted speech stimuli decreased as segment duration increased. 20-band checkerboard speech stimuli brought nearly 100% intelligibility irrespective of segment duration, whereas, with 2 and 4 frequency bands, a trough of 35%-40% appeared at the 160-ms segment duration. Mosaic speech stimuli (power was averaged over a time-frequency unit) yielded generally poor intelligibility ( ⩽10%). The results revealed the limitations of underlying auditory organization for speech cues scattered in a time-frequency domain.

Fuzzy-Based Quality Adaptation Algorithm for Improving QoE from MPEG-DASH Video

Video clients employ HTTP-based adaptive bitrate (ABR) algorithms to optimize users’ quality of experience (QoE). ABR algorithms adopt video quality based on the network conditions during playback. The existing state-of-the-art ABR algorithms ignore the fact that video streaming services deploy segment durations differently in different services, and HTTP clients offer distinct buffer sizes. The existing ABR algorithms use fixed control laws and are designed with predefined client/server settings. As a result, adaptation algorithms fail to achieve optimal performance across a variety of video client settings and QoE objectives. We propose a buffer- and segment-aware fuzzy-based ABR algorithm that selects video rates for future video segments based on segment duration and the client’s buffer size in addition to throughput and playback buffer level. We demonstrate that the proposed algorithm guarantees high QoE across various video player settings and video content characteristics. The proposed algorithm efficiently utilizes bandwidth in order to download high-quality video segments and to guarantee high QoE. The results from our experiments reveal that the proposed adaptation algorithm outperforms state-of-the-art algorithms, providing improvements in average video rate, QoE, and bandwidth utilization, respectively, of 5% to 18%, about 13% to 30%, and up to 45%.

Intelligibility of chimeric locally time-reversed speech: Relative contribution of four frequency bands.

Intelligibility of four-band speech stimuli was investigated (n = 18), such that only one of the frequency bands was preserved, whereas other bands were locally time-reversed (segment duration: 75-300 ms), or vice versa. Intelligibility was best retained (82% at 75 ms) when the second lowest band (540-1700 Hz) was preserved. When the same band was degraded, the largest drop (10% at 300 ms) occurred. The lowest and second highest bands contributed similarly less strongly to intelligibility. The highest frequency band contributed least. A close connection between the second lowest frequency band and sonority was suggested.

Variational DNN embeddings for text-independent speaker verification

• We proposed a variational-based regularization term to train DNN embeddings for speaker verification. • The regularization function measures the match between the embeddings and a given desired prior distribution. • The match is a non-parametric measure, which makes the system flexible for different desired priors. • Both Gaussian and Uniform distribution priors produce more suitable embeddings for standard PLDA scoring backend. In state-of-the-art text-independent speaker verification systems, a discriminative deep neural network (DNN) model learns speaker-discriminative representations (x-vectors) for utterances using labeled data. For the verification task, a Probabilistic Linear Discriminant Analysis (PLDA) model is used to decide whether two x-vectors come from the same speaker. The PLDA scoring model assumes Gaussian priors and conditional distributions across speakers, which is not the case for x-vectors. This work introduces a variational-based regularization term that encourages the network to generate embeddings that follow a desired prior distribution. The regularization function performs a non-parametric match between the embeddings generated in the mini-batch training and a sample from the desired distribution. Unlike Variational Auto Encoders (VAEs), no distribution parameter is necessary to be learned, and no sampling schema is employed, which makes the proposed method flexible for different desired distributions. Our experiments compared the proposed method with the standard x-vectors system jointly with other approaches recently proposed to generate Gaussianized representations. We assessed the verification performance of the systems using the Fisher English Training Speech - Part II database in eight test conditions based on the gender of the speakers and the duration of the speech segments. Besides using the standard Gaussian distribution as prior, we also applied a less strict distribution (uniform). The proposed method outperformed others in all test conditions for both distributions, with gains of performance between 7.68% and 20.49% when compared to the standard x-vectors. To understand the effect of the regularizations into the embeddings space, we also conducted a 2-dimensional visual comparison, which showed clusters with better quality when the regularizations were applied.

Scalable and Safe Multi-Agent Motion Planning with Nonlinear Dynamics and Bounded Disturbances

We present a scalable and effective multi-agent safe motion planner that enables a group of agents to move to their desired locations while avoiding collisions with obstacles and other agents, with the presence of rich obstacles, high-dimensional, nonlinear, nonholonomic dynamics, actuation limits, and disturbances. We address this problem by finding a piecewise linear path for each agent such that the actual trajectories following these paths are guaranteed to satisfy the reach-and-avoid requirement. We show that the spatial tracking error of the actual trajectories of the controlled agents can be pre-computed for any qualified path that considers the minimum duration of each path segment due to actuation limits. Using these bounds, we find a collision-free path for each agent by solving Mixed Integer-Linear Programs and coordinate agents by using the priority-based search. We demonstrate our method by benchmarking in 2D and 3D scenarios with ground vehicles and quadrotors, respectively, and show improvements over the solving time and the solution quality compared to two state-of-the-art multi-agent motion planners.

Development of AI-based method to detect the subtle ECG deviations from the population ECG norm

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Academy of Science of Ukraine Background Electrocardiogram (ECG) is still the primary source for the diagnostic and prognostic information about cardiovascular diseases. The concept of "normal ECG" parameters is crucial for the reliable diagnosis, since it provides reference for the ECG under examination. With the development of new methods and tools for ECG feature extraction and classification based on artificial intelligence (AI), it becomes possible to identify subtle changes in the heart activity to detect possible abnormalities at the early stage. The challenge of this work is to identify the deviations in ECG of clinically healthy persons from the conditional "population" norm . Methods The normal ECG is described as a feature vector composed of the time-magnitude parameters of signal-averaged ECG (SAECG). To define the subjects that possibly have variations from the "population" norm, the outlier detection approach is proposed: first the cloud of the vectors , constructed from the set of normal ECG"s , obtained from young, clinically similar healthy persons was created in feature space. Then, a particular ECG is considered deviant and requires the attention of the clinician when it is considered an outlier of the cloud of normal ECGs. In the experiment, SAECGs from the group of 139 young subjects (male, age 18-28 years) with no reported cardiovascular problems are used to extract 34 features from SAECG leads (magnitudes and durations of ECG waves, duration of ECG segments, etc.). ECGs were routinely previewed by qualified physicians, and no obvious anomalies were noticed. The Isolation Forest anomaly detection method is used with variable numbers of trees and different contamination parameters. Results The ratio of outliers were changed from 5 to 10% (7-12 subjects) with various numbers of estimator trees. Seven outlier SAECGs were repeatedly appearing for various settings. Out of these, 4 subjects were the oldest persons in group examined , and 3 others had a rare ventricular premature beats during routine ECG examination. Conclusion The proposed method is promising for application in routine and express ECG tests since it is able to quantify the subtle deviations from the normal ECG group.

Phonemic restoration of interrupted locally time-reversed speech

Intelligibility of temporally degraded speech was investigated with locally time-reversed speech (LTR) and its interrupted version (ILTR). Control stimuli comprising interrupted speech (I) were also included. Speech stimuli consisted of 200 Japanese meaningful sentences. In interrupted stimuli, speech segments were alternated with either silent gaps or pink noise bursts. The noise bursts had a level of − 10, 0 or + 10 dB relative to the speech level. Segment duration varied from 20 to 160 ms for ILTR sentences, but was fixed at 160 ms for I sentences. At segment durations between 40 and 80 ms, severe reductions in intelligibility were observed for ILTR sentences, compared with LTR sentences. A substantial improvement in intelligibility (30–33%) was observed when 40-ms silent gaps in ILTR were replaced with 0- and + 10-dB noise. Noise with a level of − 10 dB had no effect on the intelligibility. These findings show that the combined effects of interruptions and temporal reversal of speech segments on intelligibility are greater than the sum of each individual effect. The results also support the idea that illusory continuity induced by high-level noise bursts improves the intelligibility of ILTR and I sentences.

Mora in Basrah Arabic: A Morpho-Phonological approach

This paper has been written to fall within the orbit of the moraic framework of the syllable, particularly the syllable weight, of Basrah Arabic. Universal as its nature is, mora, when studied and then applied, has, metaphorically speaking, the power of casting its phonological 'spell' over the problems of the morpho-phonology of Basrah tri-segmental verbs, adjectives and nouns which have popped up in the context of investigating the behavior of Basrah syllabicity, and thus the mora 'spell' gets these problematic issues easily solvable and surmountable. The problems overcome by applying the moraic model are of two facets: some of them are phonologically-based problems and others are morphologically-based ones. Either case, mora is manipulated to throw its shadow on them equally and adequately. With this in mind, the application of moraic aspects to some Basrah verbs presupposes a drastic shift in segmental durations, namely, vowel ones when occurred word-medially. Among different results reached by this paper is that Basrah Arabic syllabic templates of certain verbs, adjectives and nouns need to be pinpointed from the mora-tier angle other than from the CV-tier and X-tier angles.

Effects of tDCS on Sound Duration in Patients with Apraxia of Speech in Primary Progressive Aphasia.

Transcranial direct current stimulation (tDCS) over the left inferior frontal gyrus (IFG) was found to improve oral and written naming in post-stroke and primary progressive aphasia (PPA), speech fluency in stuttering, a developmental speech-motor disorder, and apraxia of speech (AOS) symptoms in post-stroke aphasia. This paper addressed the question of whether tDCS over the left IFG coupled with speech therapy may improve sound duration in patients with apraxia of speech (AOS) symptoms in non-fluent PPA (nfvPPA/AOS) more than sham. Eight patients with non-fluent PPA/AOS received either active or sham tDCS, along with speech therapy for 15 sessions. Speech therapy involved repeating words of increasing syllable-length. Evaluations took place before, immediately after, and two months post-intervention. Words were segmented into vowels and consonants and the duration of each vowel and consonant was measured. Segmental duration was significantly shorter after tDCS compared to sham and tDCS gains generalized to untrained words. The effects of tDCS sustained over two months post-treatment in trained and untrained sounds. Taken together, these results demonstrate that tDCS over the left IFG may facilitate speech production by reducing segmental duration. The results provide preliminary evidence that tDCS may maximize efficacy of speech therapy in patients with nfvPPA/AOS.

The differential effects of vowel and onset consonant lengthening on speech segmentation: Evidence from Taiwanese Southern Min.

A review of previous speech segmentation research suggests the prediction that listeners of Taiwanese Southern Min (TSM), a lexical tone language, would exploit vowel lengthening and syllable-onset consonant lengthening to locate word ends and beginnings, respectively. Yet, correlations between segment duration and tone identity in tone languages along with some TSM-specific phonological phenomena may work against such use. Two artificial language learning experiments examined TSM listeners' use of the lengthening cues. The listeners heard the words of an artificial language (e.g., /ba.nu.me/) repeated continuously and identified them in a subsequent two-alternative forced-choice test. Experiment I revealed that their segmentation benefits from and only from word-initial onset lengthening or word-final vowel lengthening, supporting the prediction. Experiment II further demonstrated that these two cues in combination synergistically support segmentation at least when compared to word-initial onset lengthening alone, consistent with previous findings regarding complementary cues. These results furnish additional evidence that vowel and onset consonant lengthening affect segmentation in different ways, possibly reflecting a functional division between vowels and consonants that is supported by some prosody-computing mechanism. Additionally, vowel lengthening seems to affect segmentation to a greater extent than onset consonant lengthening. Possible explanations for this and further issues are discussed.