Improved signal analysis and time-synchronous reconstruction in waveform interpolation coding

This paper presents a waveform-matched waveform interpolation (WMWI) technique which enables improved speech analysis over existing WI coders. In WMWI, an accurate representation of speech evolution is produced by extracting critically-sampled pitch periods of a time-warped, constant pitch residual. The technique also offers waveform-matching capabilities by using an inverse warping process to near-perfectly reconstruct the residual. Here, a pitch track optimisation technique is described which ensures the speech residual can be effectively decomposed and quantised. Also, the pitch parameters required to efficiently quantise and recreate the pitch track, on a period-by-period basis, are identified. This allows time-synchrony between the original and decoded signals to be preserved

Comparison of CELP speech coder with a wavelet method

This thesis compares the speech quality of Code Excited Linear Predictor (CELP, Federal Standard 1016) speech coder with a new wavelet method to compress speech. The performances of both are compared by performing subjective listening tests. The test signals used are clean signals (i.e. with no background noise), speech signals with room noise and speech signals with artificial noise added. Results indicate that for clean signals and signals with predominantly voiced components the CELP standard performs better than the wavelet method but for signals with room noise the wavelet method performs much better than the CELP. For signals with artificial noise added, the results are mixed depending on the level of artificial noise added with CELP performing better for low level noise added signals and the wavelet method performing better for higher noise levels

Low rate WI SEW representation using a REW-implicit pulse model

Reducing the bit rate of waveform interpolation speech coders while maintaining the perceptual quality has been the focus of a great deal of research. This letter proposes a new method of slowly evolving waveform (SEW) quantization specifically targeted at low rate coding. The proposed method uses a pulse model whose parameters are implicitly contained in the quantized rapidly evolving waveform (REW) parameters, thus requiring no bits for transmission. Results indicate no degradation in perceptual speech quality when compared to that of the existing SEW quantization method. This retention of perceptual quality is in spite of a 12% reduction in the overall coder bit rate

Algorithms and architectures for the multirate additive synthesis of musical tones

In classical Additive Synthesis (AS), the output signal is the sum of a large number of independently controllable sinusoidal partials. The advantages of AS for music synthesis are well known as is the high computational cost. This thesis is concerned with the computational optimisation of AS by multirate DSP techniques. In note-based music synthesis, the expected bounds of the frequency trajectory of each partial in a finite lifecycle tone determine critical time-invariant partial-specific sample rates which are lower than the conventional rate (in excess of 40kHz) resulting in computational savings. Scheduling and interpolation (to suppress quantisation noise) for many sample rates is required, leading to the concept of Multirate Additive Synthesis (MAS) where these overheads are minimised by synthesis filterbanks which quantise the set of available sample rates. Alternative AS optimisations are also appraised. It is shown that a hierarchical interpretation of the QMF filterbank preserves AS generality and permits efficient context-specific adaptation of computation to required note dynamics. Practical QMF implementation and the modifications necessary for MAS are discussed. QMF transition widths can be logically excluded from the MAS paradigm, at a cost. Therefore a novel filterbank is evaluated where transition widths are physically excluded. Benchmarking of a hypothetical orchestral synthesis application provides a tentative quantitative analysis of the performance improvement of MAS over AS. The mapping of MAS into VLSI is opened by a review of sine computation techniques. Then the functional specification and high-level design of a conceptual MAS Coprocessor (MASC) is developed which functions with high autonomy in a loosely-coupled master- slave configuration with a Host CPU which executes filterbanks in software. Standard hardware optimisation techniques are used, such as pipelining, based upon the principle of an application-specific memory hierarchy which maximises MASC throughput

Optimisation techniques for low bit rate speech coding

This thesis extends the background theory of speech and major speech coding schemes used in existing networks to an implementation of GSM full-rate speech compression on a RISC DSP and a multirate application for speech coding. Speech coding is the field concerned with obtaining compact digital representations of speech signals for the purpose of efficient transmission. In this thesis, the background of speech compression, characteristics of speech signals and the DSP algorithms used have been examined. The current speech coding schemes and requirements have been studied. The Global System for Mobile communication (GSM) is a digital mobile radio system which is extensively used throughout Europe, and also in many other parts of the world. The algorithm is standardised by the European Telecommunications Standardisation histitute (ETSI). The full-rate and half-rate speech compression of GSM have been analysed. A real time implementation of the full-rate algorithm has been carried out on a RISC processor GEPARD by Austria Mikro Systeme International (AMS). The GEPARD code has been tested with all of the test sequences provided by ETSI and the results are bit-exact. The transcoding delay is lower than the ETSI requirement. A comparison of the half-rate and full-rate compression algorithms is discussed. Both algorithms offer near toll speech quality comparable or better than analogue cellular networks. The half-rate compression requires more computationally intensive operations and therefore a more powerful processor will be needed due to the complexity of the code. Hence the cost of the implementation of half-rate codec will be considerably higher than full-rate. A description of multirate signal processing and its application on speech (SBC) and speech/audio (MPEG) has been given. An investigation into the possibility of combining multirate filtering and GSM fill-rate speech algorithm. The results showed that multirate signal processing cannot be directly applied GSM full-rate speech compression since this method requires more processing power, causing longer coding delay but did not appreciably improve the bit rate. In order to achieve a lower bit rate, the GSM full-rate mathematical algorithm can be used instead of the standardised ETSI recommendation. Some changes including the number of quantisation bits has to be made before the application of multirate signal processing and a new standard will be required

A software based, 13 kbits/s real-time internet codec

Due to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to [email protected], referencing the URI of the item.Includes bibliographical references: p. 50-53.Issued also on microfiche from Lange Micrographics.Bandwidth usage is a prime concern to many on the Internet, especially for users on low bit rate channels. As video conferencing becomes more popular, the need for efficient software based compression of video and audio becomes more important. This work develops a scalable, real-time, software based speech codec for use on desktop computers. The system is based on subband coding, adaptive prediction, and Huffman coding, and is capable of bit rates below 13 kbits/s for communications quality audio. The quality may be 'scaled" up by allocating additional bits to the subbands. This coder has been successfully implemented in real-time on a Sun Sparc 10 platform

A Perceptual Representation of Audio

The human auditory system performs many remarkable feats; we only fully appreciate how sophisticated these are when we try to simulate them on a computer. Through building such computer models, we gain insight into perceptual processing in general, and develop useful new ways to analyze signals. This thesis describes a transformation of sound into a representation with various properties specifically oriented towards simulations of source separation. Source separation denotes the ability of listeners to perceive sound originating from a particular origin as separate from simultaneous interfering sounds. An example would be following the notes of a single instrument while listening to an orchestra. Using a cochlea-inspired filterbank and strategies of peak-picking and track-formation, the representation organizes time-frequency energy into distinct elements; these are argued to correspond to indivisible components of the perception. The elements contain information such as fine time structure which is important to perceptual quality and source separability. A high quality resynthesis method is described which gives good results even for modified representations. The performance and results of the analysis and synthesis methods are discussed, and the intended applications of the new domain are described in detail. This description also explains how the principles of source separation, as established by previous research in psychoacoustics, will be applied as the next step towards a fully functional source separator

Noise Robust Pitch Tracking by Subband Autocorrelation Classification

Speech pitch tracking is one of the elementary tasks of the Computational Auditory Scene Analysis (CASA). While a human can easily listen to the voiced pitch in highly noisy recordings, the performance of automatic speech pitch tracking degrades in unknown noisy audio conditions. Traditional pitch trackers use either autocorrelation or the Fourier transform to calculate periodicity, which works well for clean recordings. For noisy recordings, however, the accuracy of these pitch trackers degrades in general. For example, the information in parts of the frequency spectrum may be lost due to analog radio band transmission and/or contain additive noise of various kinds. Instead of explicitly using the most obvious features of autocorrelation, we propose a trained classier-based approach, which we call Subband Autocorrelation Classification (SAcC). A multi-layer perceptron (MLP) classier is trained on the principal components of the autocorrelations of subbands from an auditory filterbank. The output of the MLP classifier is temporally smoothed to produce the pitch track by finding the Viterbi path of a Hidden Markov Model (HMM). Training on various types of noisy speech recordings leads to a great increase in performance over state-of-the-art algorithms, according to both the traditional Gross Pitch Error (GPE) measure, and a proposed novel Pitch Tracking Error (PTE) which more fully reflects the accuracy of both pitch estimation/extraction and voicing detection in a single measure. To verify the generalization and specificity of SAcC, we test SAcC on a real world problem that has a large-scale noisy speech corpus. The data is from the DARPA Robust Automatic Transcription of Speech (RATS) program. The experiments on the performance evaluation of SAcC pitch tracking confirm the generalization power of SAcC across various unknown noise conditions and distinct speech corpora. We also report the use of SAcC output adds a significant improvement to a Speaker Identification (SID) system for RATS as well, suggesting the potential contribution of SAcC pitch tracking in the higher-level tasks

Perceptual models in speech quality assessment and coding

The ever-increasing demand for good communications/toll quality speech has created a renewed interest into the perceptual impact of rate compression. Two general areas are investigated in this work, namely speech quality assessment and speech coding. In the field of speech quality assessment, a model is developed which simulates the processing stages of the peripheral auditory system. At the output of the model a "running" auditory spectrum is obtained. This represents the auditory (spectral) equivalent of any acoustic sound such as speech. Auditory spectra from coded speech segments serve as inputs to a second model. This model simulates the information centre in the brain which performs the speech quality assessment. [Continues.