A robust low bit rate quad-band excitation LSP vocoder.

by Chiu Kim Ming.Thesis (M.Phil.)--Chinese University of Hong Kong, 1994.Includes bibliographical references (leaves 103-108).Chapter Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Speech production --- p.2Chapter 1.2 --- Low bit rate speech coding --- p.4Chapter Chapter 2 --- Speech analysis & synthesis --- p.8Chapter 2.1 --- Linear prediction of speech signal --- p.8Chapter 2.2 --- LPC vocoder --- p.11Chapter 2.2.1 --- Pitch and voiced/unvoiced decision --- p.11Chapter 2.2.2 --- Spectral envelope representation --- p.15Chapter 2.3 --- Excitation --- p.16Chapter 2.3.1 --- Regular pulse excitation and Multipulse excitation --- p.16Chapter 2.3.2 --- Coded excitation and vector sum excitation --- p.19Chapter 2.4 --- Multiband excitation --- p.22Chapter 2.5 --- Multiband excitation vocoder --- p.25Chapter Chapter 3 --- Dual-band and Quad-band excitation --- p.31Chapter 3.1 --- Dual-band excitation --- p.31Chapter 3.2 --- Quad-band excitation --- p.37Chapter 3.3 --- Parameters determination --- p.41Chapter 3.3.1 --- Pitch detection --- p.41Chapter 3.3.2 --- Voiced/unvoiced pattern generation --- p.43Chapter 3.4 --- Excitation generation --- p.47Chapter Chapter 4 --- A low bit rate Quad-Band Excitation LSP Vocoder --- p.51Chapter 4.1 --- Architecture of QBELSP vocoder --- p.51Chapter 4.2 --- Coding of excitation parameters --- p.58Chapter 4.2.1 --- Coding of pitch value --- p.58Chapter 4.2.2 --- Coding of voiced/unvoiced pattern --- p.60Chapter 4.3 --- Spectral envelope estimation and coding --- p.62Chapter 4.3.1 --- Spectral envelope & the gain value --- p.62Chapter 4.3.2 --- Line Spectral Pairs (LSP) --- p.63Chapter 4.3.3 --- Coding of LSP frequencies --- p.68Chapter 4.3.4 --- Coding of gain value --- p.77Chapter Chapter 5 --- Performance evaluation --- p.80Chapter 5.1 --- Spectral analysis --- p.80Chapter 5.2 --- Subjective listening test --- p.93Chapter 5.2.1 --- Mean Opinion Score (MOS) --- p.93Chapter 5.2.2 --- Diagnostic Rhyme Test (DRT) --- p.96Chapter Chapter 6 --- Conclusions and discussions --- p.99References --- p.103Appendix A Subroutine of pitch detection --- p.A-I - A-IIIAppendix B Subroutine of voiced/unvoiced decision --- p.B-I - B-VAppendix C Subroutine of LPC coefficients calculation using Durbin's recursive method --- p.C-I - C-IIAppendix D Subroutine of LSP calculation using Chebyshev Polynomials --- p.D-I - D-IIIAppendix E Single syllable word pairs for Diagnostic Rhyme Test --- p.E-

Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression

A configurable vector processor for accelerating speech coding algorithms

The growing demand for voice-over-packer (VoIP) services and multimedia-rich applications has made increasingly important the efficient, real-time implementation of low-bit rates speech coders on embedded VLSI platforms. Such speech coders are designed to substantially reduce the bandwidth requirements thus enabling dense multichannel gateways in small form factor. This however comes at a high computational cost which mandates the use of very high performance embedded processors. This thesis investigates the potential acceleration of two major ITU-T speech coding algorithms, namely G.729A and G.723.1, through their efficient implementation on a configurable extensible vector embedded CPU architecture. New scalar and vector ISAs were introduced which resulted in up to 80% reduction in the dynamic instruction count of both workloads. These instructions were subsequently encapsulated into a parametric, hybrid SISD (scalar processor)–SIMD (vector) processor. This work presents the research and implementation of the vector datapath of this vector coprocessor which is tightly-coupled to a Sparc-V8 compliant CPU, the optimization and simulation methodologies employed and the use of Electronic System Level (ESL) techniques to rapidly design SIMD datapaths

Domain-optimized Chinese speech generation.

Fung Tien Ying.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 119-128).Abstracts in English and Chinese.Abstract --- p.1Acknowledgement --- p.1List of Figures --- p.7List of Tables --- p.11Chapter 1 --- Introduction --- p.14Chapter 1.1 --- General Trends on Speech Generation --- p.15Chapter 1.2 --- Domain-Optimized Speech Generation in Chinese --- p.16Chapter 1.3 --- Thesis Organization --- p.17Chapter 2 --- Background --- p.19Chapter 2.1 --- Linguistic and Phonological Properties of Chinese --- p.19Chapter 2.1.1 --- Articulation --- p.20Chapter 2.1.2 --- Tones --- p.21Chapter 2.2 --- Previous Development in Speech Generation --- p.22Chapter 2.2.1 --- Articulatory Synthesis --- p.23Chapter 2.2.2 --- Formant Synthesis --- p.24Chapter 2.2.3 --- Concatenative Synthesis --- p.25Chapter 2.2.4 --- Existing Systems --- p.31Chapter 2.3 --- Our Speech Generation Approach --- p.35Chapter 3 --- Corpus-based Syllable Concatenation: A Feasibility Test --- p.37Chapter 3.1 --- Capturing Syllable Coarticulation with Distinctive Features --- p.39Chapter 3.2 --- Creating a Domain-Optimized Wavebank --- p.41Chapter 3.2.1 --- Generate-and-Filter --- p.44Chapter 3.2.2 --- Waveform Segmentation --- p.47Chapter 3.3 --- The Use of Multi-Syllable Units --- p.49Chapter 3.4 --- Unit Selection for Concatenative Speech Output --- p.50Chapter 3.5 --- A Listening Test --- p.51Chapter 3.6 --- Chapter Summary --- p.52Chapter 4 --- Scalability and Portability to the Stocks Domain --- p.55Chapter 4.1 --- Complexity of the ISIS Responses --- p.56Chapter 4.2 --- XML for input semantic and grammar representation --- p.60Chapter 4.3 --- Tree-Based Filtering Algorithm --- p.63Chapter 4.4 --- Energy Normalization --- p.67Chapter 4.5 --- Chapter Summary --- p.69Chapter 5 --- Investigation in Tonal Contexts --- p.71Chapter 5.1 --- The Nature of Tones --- p.74Chapter 5.1.1 --- Human Perception of Tones --- p.75Chapter 5.2 --- Relative Importance of Left and Right Tonal Context --- p.77Chapter 5.2.1 --- Tonal Contexts in the Date-Time Subgrammar --- p.77Chapter 5.2.2 --- Tonal Contexts in the Numeric Subgrammar --- p.82Chapter 5.2.3 --- Conclusion regarding the Relative Importance of Left versus Right Tonal Contexts --- p.86Chapter 5.3 --- Selection Scheme for Tonal Variants --- p.86Chapter 5.3.1 --- Listening Test for our Tone Backoff Scheme --- p.90Chapter 5.3.2 --- Error Analysis --- p.92Chapter 5.4 --- Chapter Summary --- p.94Chapter 6 --- Summary and Future Work --- p.95Chapter 6.1 --- Contributions --- p.97Chapter 6.2 --- Future Directions --- p.98Chapter A --- Listening Test Questionnaire for FOREX Response Genera- tion --- p.100Chapter B --- Major Response Types For ISIS --- p.102Chapter C --- Recording Corpus for Tone Investigation in Date-time Sub- grammar --- p.105Chapter D --- Statistical Test for Left Tonal Context --- p.109Chapter E --- Statistical Test for Right Tonal Context --- p.112Chapter F --- Listening Test Questionnaire for Backoff Unit Selection Scheme --- p.115Chapter G --- Statistical Test for the Backoff Unit Selection Scheme --- p.117Chapter H --- Statistical Test for the Backoff Unit Selection Scheme --- p.118Bibliography --- p.11

Analysis of speech and other sounds

This thesis comprises a study of various types of signal processing techniques, applied to the tasks of extracting information from speech, cough, and dolphin sounds. Established approaches to analysing speech sounds for the purposes of low data rate speech encoding, and more generally to determine the characteristics of the speech signal, are reviewed. Two new speech processing techniques, shift-and-add and CLEAN (which have previously been applied in the field of astronomical image processing), are developed and described in detail. Shift-and-add is shown to produce a representation of the long-term "average" characteristics of the speech signal. Under certain simplifying assumptions, this can be equated to the average glottal excitation. The iterative deconvolution technique called CLEAN is employed to deconvolve the shift-and-add signal from the speech signal. Because the resulting "CLEAN" signal has relatively few non-zero samples, it can be directly encoded at a low data rate. The performance of a low data rate speech encoding scheme that takes advantage of this attribute of CLEAN is examined in detail. Comparison with the multi-pulse LP C approach to speech coding shows that the new method provides similar levels of performance at medium data rates of about 16kbit/s. The changes that occur in the character of a person's cough sounds when that person is afflicted with asthma are outlined. The development and implementation of a micro-computer-based cough sound analysis system, designed to facilitate the ongoing study of these sounds, is described. The system performs spectrographic analysis on the cough sounds. A graphical user interface allows the sound waveforms and spectra to be displayed and examined in detail. Preliminary results are presented, which indicate that the spectral content of cough sounds are changed by asthma. An automated digital approach to studying the characteristics of Hector's dolphin vocalisations is described. This scheme characterises the sounds by extracting descriptive parameters from their time and frequency domain envelopes. The set of parameters so obtained from a sample of click sequences collected from free-ranging dolphins is analysed by principal component analysis. Results are presented which indicate that Hector's dolphins produce only a small number of different vocal sounds. In addition to the statistical analysis, several of the clicks, which are assumed to be used for echo-location, are analysed in terms of their range-velocity ambiguity functions. The results suggest that Hector's dolphins can distinguish targets separated in range by about 2cm, but are unable to separate targets that differ only in their velocity