Journal•ISSN: 0167-6393
Speech Communication
Elsevier BV
About: Speech Communication is an academic journal published by Elsevier BV. The journal publishes majorly in the area(s): Speech processing & Speech synthesis. It has an ISSN identifier of 0167-6393. Over the lifetime, 2658 publications have been published receiving 119028 citations.
Topics: Speech processing, Speech synthesis, Speech enhancement, Hidden Markov model, Intelligibility (communication)
Papers published on a yearly basis
Papers
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TL;DR: NoISEX-92 specifies a carefully controlled experiment on artificially noisy speech data, examining performance for a limited digit recognition task but with a relatively wide range of noises and signal-to-noise ratios.
Abstract: The NOISEX-92 experiment and database is described and discussed. NOISEX-92 specifies a carefully controlled experiment on artificially noisy speech data, examining performance for a limited digit recognition task but with a relatively wide range of noises and signal-to-noise ratios. Example recognition results are given.
1,960 citations
TL;DR: A set of simple new procedures has been developed to enable the real-time manipulation of speech parameters by using pitch-adaptive spectral analysis combined with a surface reconstruction method in the time–frequency region.
Abstract: A set of simple new procedures has been developed to enable the real-time manipulation of speech parameters. The proposed method uses pitch-adaptive spectral analysis combined with a surface reconstruction method in the time–frequency region. The method also consists of a fundamental frequency (F0) extraction using instantaneous frequency calculation based on a new concept called `fundamentalness'. The proposed procedures preserve the details of time–frequency surfaces while almost perfectly removing fine structures due to signal periodicity. This close-to-perfect elimination of interferences and smooth F0 trajectory allow for over 600% manipulation of such speech parameters as pitch, vocal tract length, and speaking rate, while maintaining high reproductive quality.
1,741 citations
TL;DR: It is suggested to use the Brunswikian lens model as a base for research on the vocal communication of emotion, which allows one to model the complete process, including both encoding, transmission, and decoding of vocal emotion communication.
Abstract: The current state of research on emotion effects on voice and speech is reviewed and issues for future research efforts are discussed. In particular, it is suggested to use the Brunswikian lens model as a base for research on the vocal communication of emotion. This approach allows one to model the complete process, including both encoding (expression), transmission, and decoding (impression) of vocal emotion communication. Special emphasis is placed on the conceptualization and operationalization of the major elements of the model (i.e., the speaker's emotional state, the listener's attribution, and the mediating acoustic cues). In addition, the advantages and disadvantages of research paradigms for the induction or observation of emotional expression in voice and speech and the experimental manipulation of vocal cues are discussed, using pertinent examples drawn from past and present research.
1,674 citations
TL;DR: In a common framework several algorithms that have been proposed recently, in order to improve the voice quality of a text-to-speech synthesis based on acoustical units concatenation based on pitch-synchronous overlap-add approach are reviewed.
Abstract: We review in a common framework several algorithms that have been proposed recently, in order to improve the voice quality of a text-to-speech synthesis based on acoustical units concatenation (Charpentier and Moulines, 1988; Moulines and Charpentier, 1988; Hamon et al., 1989). These algorithms rely on a pitch-synchronous overlap-add (PSOLA) approach for modifying the speech prosody and concatenating speech waveforms. The modifications of the speech signal are performed either in the frequency domain (FD-PSOLA), using the Fast Fourier Transform, or directly in the time domain (TD-PSOLA), depending on the length of the window used in the synthesis process. The frequency domain approach is capable of a great flexibility in modifying the spectral characteristics of the speech signal, while the time domain approach provides very efficient solutions for the real time implementation of synthesis systems. We also discuss the different kinds of distortions involved in these different algorithms.
1,438 citations
TL;DR: This paper starts with the fundamentals of automatic speaker recognition, concerning feature extraction and speaker modeling and elaborate advanced computational techniques to address robustness and session variability.
Abstract: This paper gives an overview of automatic speaker recognition technology, with an emphasis on text-independent recognition. Speaker recognition has been studied actively for several decades. We give an overview of both the classical and the state-of-the-art methods. We start with the fundamentals of automatic speaker recognition, concerning feature extraction and speaker modeling. We elaborate advanced computational techniques to address robustness and session variability. The recent progress from vectors towards supervectors opens up a new area of exploration and represents a technology trend. We also provide an overview of this recent development and discuss the evaluation methodology of speaker recognition systems. We conclude the paper with discussion on future directions.
1,433 citations