Speech Coding 2
HomeFull List of Titles
1: ICSLP'98 Proceedings
Keynote SpeechesText-To-Speech Synthesis 1Spoken Language Models and Dialog 1Prosody and Emotion 1Hidden Markov Model Techniques 1Speaker and Language Recognition 1Multimodal Spoken Language Processing 1Isolated Word RecognitionRobust Speech Processing in Adverse Environments 1Spoken Language Models and Dialog 2Articulatory Modelling 1Talking to Infants, Pets and LoversRobust Speech Processing in Adverse Environments 2Spoken Language Models and Dialog 3Speech Coding 1Articulatory Modelling 2Prosody and Emotion 2Neural Networks, Fuzzy and Evolutionary Methods 1Utterance Verification and Word Spotting 1 / Speaker Adaptation 1Text-To-Speech Synthesis 2Spoken Language Models and Dialog 4Human Speech Perception 1Robust Speech Processing in Adverse Environments 3Speech and Hearing Disorders 1Prosody and Emotion 3Spoken Language Understanding Systems 1Signal Processing and Speech Analysis 1Spoken Language Generation and Translation 1Spoken Language Models and Dialog 5Segmentation, Labelling and Speech Corpora 1Multimodal Spoken Language Processing 2Prosody and Emotion 4Neural Networks, Fuzzy and Evolutionary Methods 2Large Vocabulary Continuous Speech Recognition 1Speaker and Language Recognition 2Signal Processing and Speech Analysis 2Prosody and Emotion 5Robust Speech Processing in Adverse Environments 4Segmentation, Labelling and Speech Corpora 2Speech Technology Applications and Human-Machine Interface 1Large Vocabulary Continuous Speech Recognition 2Text-To-Speech Synthesis 3Language Acquisition 1Acoustic Phonetics 1Speaker Adaptation 2Speech Coding 2Hidden Markov Model Techniques 2Multilingual Perception and Recognition 1Large Vocabulary Continuous Speech Recognition 3Articulatory Modelling 3Language Acquisition 2Speaker and Language Recognition 3Text-To-Speech Synthesis 4Spoken Language Understanding Systems 4Human Speech Perception 2Large Vocabulary Continuous Speech Recognition 4Spoken Language Understanding Systems 2Signal Processing and Speech Analysis 3Human Speech Perception 3Speaker Adaptation 3Spoken Language Understanding Systems 3Multimodal Spoken Language Processing 3Acoustic Phonetics 2Large Vocabulary Continuous Speech Recognition 5Speech Coding 3Language Acquisition 3 / Multilingual Perception and Recognition 2Segmentation, Labelling and Speech Corpora 3Text-To-Speech Synthesis 5Spoken Language Generation and Translation 2Human Speech Perception 4Robust Speech Processing in Adverse Environments 5Text-To-Speech Synthesis 6Speech Technology Applications and Human-Machine Interface 2Prosody and Emotion 6Hidden Markov Model Techniques 3Speech and Hearing Disorders 2 / Speech Processing for the Speech and Hearing Impaired 1Human Speech ProductionSegmentation, Labelling and Speech Corpora 4Speaker and Language Recognition 4Speech Technology Applications and Human-Machine Interface 3Utterance Verification and Word Spotting 2Large Vocabulary Continuous Speech Recognition 6Neural Networks, Fuzzy and Evolutionary Methods 3Speech Processing for the Speech-Impaired and Hearing-Impaired 2Prosody and Emotion 72: SST Student Day
SST Student Day - Poster Session 1SST Student Day - Poster Session 2Author Index
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Towards a Unified Model for Low Bit-Rate Speech Coding Using a Recognition-Synthesis Approach
Authors:
Wendy J. Holmes, DERA (U.K.)
Page (NA) Paper number 553
Abstract:
This paper proposes a recognition-synthesis approach to speech coding which uses a formant trajectory model for both recognition and synthesis. It is argued that this unified approach to coding has the potential to achieve low data rates whilst preserving speech quality and paralinguistic information. A simple coding scheme is described which establishes the principles of this approach. Formant analysis is applied to the input speech, and the formant features are input to a linear-trajectory segmental hidden Markov model recognizer to locate segment boundaries. The formant parameters for each segment are coded using a linear trajectory description, and used to drive a parallel-formant synthesizer to reproduce the utterance at the receiver. The coding method has been tested on utterances from a variety of speakers. In the current system, which has not yet been optimised for coding efficiency, speech is typically coded at 600-1000 bits/s with good intelligibility, whilst preserving speaker characteristics.
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On the Significance of Temporal Masking in Speech Coding
Authors:
Jan Skoglund, Chalmers University of Technology, Department of Signals and Systems (Sweden)
W. Bastiaan Kleijn, Royal Institute of Technology, Department of Speech, Music and Hearing (Sweden)
Page (NA) Paper number 747
Abstract:
This paper addresses the issue of masking of noise in voiced speech. First, we examine the audibility of cyclostationary narrow-band noise added to voiced speech generated by synthetic excitation. Varying the temporal location of noise within a pitch cycle corresponds to varying its phase spectrum. Using this fact, we find that a phase change of the noise in the high frequency region is more perceptible for a low-pitched sound than for a high-pitched sound. We propose a pitch-dependent temporal weighting function and we show experimentally that it is beneficial to the quantization of pitch-cycle waveforms.
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Waveform Interpolation Coding With Pitch-Spaced Subbands
Authors:
W. Bastiaan Kleijn, KTH (Royal Institute of Technology) (Sweden)
Huimin Yang, Tsinghua University (China)
Ed F. Deprettere, Delft University of Technology (The Netherlands)
Page (NA) Paper number 1069
Abstract:
We present new waveform-interpolation coding procedures which allow perfect reconstruction of the speech signal from the unquantized parameter set. Instead of using adaptive parameter extraction methods, we combine a time warping of the original signal with nonadaptive parameter extraction methods. The new coding structure has good performance at low bit rates and provides convergence to the original waveform with increasing rate.
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An Improved Decomposition Method For WI Using IIR Wavelet Filter Banks
Authors:
Nicola R. Chong, University of Wollongong (Australia)
Ian S. Burnett, University of Wollongong (Australia)
Joe F. Chicharo, University of Wollongong (Australia)
Page (NA) Paper number 142
Abstract:
In this paper, we present an alternative characteristic waveform (CW) decomposition mechanism for the Waveform Interpolation (WI) paradigm based on the Pitch Synchronous Wavelet Transform (PSWT). In this technique, IIR filters replace the conventional FIR filters of the PSWT, offering computational and spectral magnitude performance advantages, in addition to significant delay reductions. Previously, the PSWT has only incorporated filter banks with slowly reacting FIR wavelet filters. While these filters possess the desirable properties of linear phase, and design simplicity, a large delay is incurred which increases exponentially with increasing resolution. The progression to IIR filter banks gives rise to a multi-resolution decomposition mechanism, beneficial for real-time applications, such as speech coding, where delay is an important issue.