CLOSE—A Data-Driven Approach to Speech Separation

This paper studies single-channel speech separation, assuming unknown, arbitrary temporal dynamics for the speech signals to be separated. A data-driven approach is described, which matches each mixed speech segment against a composite training segment to separate the underlying clean speech segments. To advance the separation accuracy, the new approach seeks and separates the longest mixed speech segments with matching composite training segments. Lengthening the mixed speech segments to match reduces the uncertainty of the constituent training segments, and hence the error of separation. For convenience, we call the new approach Composition of Longest Segments, or CLOSE. The CLOSE method includes a data-driven approach to model long-range temporal dynamics of speech signals, and a statistical approach to identify the longest mixed speech segments with matching composite training segments. Experiments are conducted on the Wall Street Journal database, for separating mixtures of two simultaneous large-vocabulary speech utterances spoken by two different speakers. The results are evaluated using various objective and subjective measures, including the challenge of large-vocabulary continuous speech recognition. It is shown that the new separation approach leads to significant improvement in all these measures.

Wide Matching - An Approach to Improving Noise Robustness for Speech Enhancement

It is shown that under certain conditions it is possible to obtain a good speech estimate from noise without requiring noise estimation. We study an implementation of the theory, namely wide matching, for speech enhancement. The new approach performs sentence-wide joint speech segment estimation subject to maximum recognizability to gain noise robustness. Experiments have been conducted to evaluate the new approach with variable noises and SNRs from -5 dB to noise free. It is shown that the new approach, without any estimation of the noise, significantly outperformed conventional methods in the low SNR conditions while retaining comparable performance in the high SNR conditions. It is further suggested that the wide matching and deep learning approaches can be combined towards a highly robust and accurate speech estimator.

Kalman tracking linear predictor for vowel intelligibility enhancement on european portuguese HMM based speech synthesis

The recent developments on Hidden Markov Models (HMM) based speech synthesis showed that this is a promising technology fully capable of competing with other established techniques. However some issues still lack a solution. Several authors report an over-smoothing phenomenon on both time and frequencies which decreases naturalness and sometimes intelligibility. In this work we present a new vowel intelligibility enhancement algorithm that uses a discrete Kalman filter (DKF) for tracking frame based parameters. The inter-frame correlations are modelled by an autoregressive structure which provides an underlying time frame dependency and can improve time-frequency resolution. The system’s performance has been evaluated using objective and subjective tests and the proposed methodology has led to improved results.

The effects of difficulty and gain versus loss on vocal physiology and acoustics

To examine the basis of emotional changes to the voice, physiological and electroglottal measures were combined with acoustic speech analysis of 30 men performing a computer task in which they lost or gained points under two levels of difficulty. Predictions of the main effects of difficulty and reward on the voice were not borne out by the data. Instead, vocal changes depended largely on interactions between gain versus loss and difficulty. The rate at which the vocal folds open and close (fundamental frequency; f0) was higher for loss than for gain when difficulty was high, but not when difficulty was low. Electroglottal measures revealed that f0 changes corresponded to shorter glottal open times for the loss conditions. Longer closed and shorter open phases were consistent with raised laryngeal tension in difficult loss conditions. Similarly, skin conductance indicated higher sympathetic arousal in loss than gain conditions, particularly when difficulty was high. The results provide evidence of the physiological basis of affective vocal responses, confirming the utility of measuring physiology and voice in the study of emotion.

Binaural prediction of speech intelligibility in reverberant rooms with multiple noise sources

When speech is in competition with interfering sources in rooms, monaural indicators of intelligibility fail to take account of the listener’s abilities to separate target speech from interfering sounds using the binaural system. In order to incorporate these segregation abilities and their susceptibility to reverberation, Lavandier and Culling [J. Acoust. Soc. Am. 127, 387–399 (2010)] proposed a model which combines effects of better-ear listening and binaural unmasking. A computationally efficient version of this model is evaluated here under more realistic conditions that include head shadow, multiple stationary noise sources, and real-room acoustics. Three experiments are presented in which speech reception thresholds were measured in the presence of one to three interferers using real-room listening over headphones, simulated by convolving anechoic stimuli with binaural room impulse-responses measured with dummy-head transducers in five rooms. Without fitting any parameter of the model, there was close correspondence between measured and predicted differences in threshold across all tested conditions. The model’s components of better-ear listening and binaural unmasking were validated both in isolation and in combination. The computational efficiency of this prediction method allows the generation of complex “intelligibility maps” from room designs. © 2012 Acoustical Society of America

Assessment of PD Speech Anomalies @ Home

Background: Voice processing in real-time is challenging. A drawback of previous work for Hypokinetic Dysarthria (HKD) recognition is the requirement of controlled settings in a laboratory environment. A personal digital assistant (PDA) has been developed for home assessment of PD patients. The PDA offers sound processing capabilities, which allow for developing a module for recognition and quantification HKD. Objective: To compose an algorithm for assessment of PD speech severity in the home environment based on a review synthesis. Methods: A two-tier review methodology is utilized. The first tier focuses on real-time problems in speech detection. In the second tier, acoustics features that are robust to medication changes in Levodopa-responsive patients are investigated for HKD recognition. Keywords such as Hypokinetic Dysarthria , and Speech recognition in real time were used in the search engines. IEEE explorer produced the most useful search hits as compared to Google Scholar, ELIN, EBRARY, PubMed and LIBRIS. Results: Vowel and consonant formants are the most relevant acoustic parameters to reflect PD medication changes. Since relevant speech segments (consonants and vowels) contains minority of speech energy, intelligibility can be improved by amplifying the voice signal using amplitude compression. Pause detection and peak to average power rate calculations for voice segmentation produce rich voice features in real time. Enhancements in voice segmentation can be done by inducing Zero-Crossing rate (ZCR). Consonants have high ZCR whereas vowels have low ZCR. Wavelet transform is found promising for voice analysis since it quantizes non-stationary voice signals over time-series using scale and translation parameters. In this way voice intelligibility in the waveforms can be analyzed in each time frame. Conclusions: This review evaluated HKD recognition algorithms to develop a tool for PD speech home-assessment using modern mobile technology. An algorithm that tackles realtime constraints in HKD recognition based on the review synthesis is proposed. We suggest that speech features may be further processed using wavelet transforms and used with a neural network for detection and quantification of speech anomalies related to PD. Based on this model, patients' speech can be automatically categorized according to UPDRS speech ratings.

Effects of hearing protector devices on speech intelligibility

The purpose of this study was to determine the influence of hearing protection devices (HPDs) on the understanding of speech in young adults with normal hearing, both in a silent situation and in the presence of ambient noise. The experimental research was carried out with the following variables: five different conditions of HPD use (without protectors, with two earplugs and with two earmuffs); a type of noise (pink noise); 4 test levels (60, 70, 80 and 90 dB[A]); 6 signal/noise ratios (without noise, + 5, + 10, zero, - 5 and - 10 dB); 5 repetitions for each case, totalling 600 tests with 10 monosyllables in each one. The variable measure was the percentage of correctly heard words (monosyllabic) in the test. The results revealed that, at the lowest levels (60 and 70 dB), the protectors reduced the intelligibility of speech (compared to the tests without protectors) while, in the presence of ambient noise levels of 80 and 90 dB and unfavourable signal/noise ratios (0, -5 and -10 dB), the HPDs improved the intelligibility. A comparison of the effectiveness of earplugs versus earmuffs showed that the former offer greater efficiency in respect to the recognition of speech, providing a 30% improvement over situations in which no protection is used. As might be expected, this study confirmed that the protectors' influence on speech intelligibility is related directly to the spectral curve of the protector's attenuation. (C) 2003 Elsevier B.V. Ltd. All rights reserved.

Producing turbulent speech sounds in the context of cleft palate.

Aims and Scope: No sound class requires so much basic knowledge of phonology, acoustics, aerodynamics, and speech production as obstruents (turbulent sounds) do. This book is intended to bridge a gap by introducing the reader to the world of obstruents from a multidisciplinary perspective. It starts with a review of typological processes, continues with various contributions to the phonetics-phonology interface, explains the realization of specific turbulent sounds in endangered languages, and finishes with surveys of obstruents from a sociophonetic, physical and pathological perspective.