Estimating acoustic speech features in low signal-to-noise ratios using a statistical framework

Accurate estimation of acoustic speech features from noisy speech and from different speakers is an ongoing problem in speech processing. Many methods have been proposed to estimate acoustic features but errors increase as signal-to-noise ratios fall. This work proposes a robust statistical framework to estimate an acoustic speech vector (comprising voicing, fundamental frequency and spectral envelope) from an intermediate feature that is extracted from a noisy time-domain speech signal. The initial approach is accurate in clean conditions but deteriorates in noise and with changing speaker. Adaptation methods are then developed to adjust the acoustic models to the noise conditions and speaker. Evaluations are carried out in stationary and nonstationary noises and at SNRs from -5dB to clean conditions. Comparison with conventional methods of estimating fundamental frequency, voicing and spectral envelope reveals the proposed framework to have lowest errors in all conditions tested

Frequency Domain Methods for Coding the Linear Predictive Residual of Speech Signals

The most frequently used speech coding paradigm is ACELP, famous because it encodes speech with high quality, while consuming a small bandwidth. ACELP performs linear prediction filtering in order to eliminate the effect of the spectral envelope from the signal. The noise-like excitation is then encoded using algebraic codebooks. The search of this codebook, however, can not be performed optimally with conventional encoders due to the correlation between their samples. Because of this, more complex algorithms are required in order to maintain the quality. Four different transformation algorithms have been implemented (DCT, DFT, Eigenvalue decomposition and Vandermonde decomposition) in order to decorrelate the samples of the innovative excitation in ACELP. These transformations have been integrated in the ACELP of the EVS codec. The transformed innovative excitation is coded using the envelope based arithmetic coder. Objective and subjective tests have been carried out to evaluate the quality of the encoding, the degree of decorrelation achieved by the transformations and the computational complexity of the algorithms

Quantisation mechanisms in multi-protoype waveform coding

Prototype Waveform Coding is one of the most promising methods for speech coding at low bit rates over telecommunications networks. This thesis investigates quantisation mechanisms in Multi-Prototype Waveform (MPW) coding, and two prototype waveform quantisation algorithms for speech coding at bit rates of 2.4kb/s are proposed. Speech coders based on these algorithms have been found to be capable of producing coded speech with equivalent perceptual quality to that generated by the US 1016 Federal Standard CELP-4.8kb/s algorithm. The two proposed prototype waveform quantisation algorithms are based on Prototype Waveform Interpolation (PWI). The first algorithm is in an open loop architecture (Open Loop Quantisation). In this algorithm, the speech residual is represented as a series of prototype waveforms (PWs). The PWs are extracted in both voiced and unvoiced speech, time aligned and quantised and, at the receiver, the excitation is reconstructed by smooth interpolation between them. For low bit rate coding, the PW is decomposed into a slowly evolving waveform (SEW) and a rapidly evolving waveform (REW). The SEW is coded using vector quantisation on both magnitude and phase spectra. The SEW codebook search is based on the best matching of the SEW and the SEW codebook vector. The REW phase spectra is not quantised, but it is recovered using Gaussian noise. The REW magnitude spectra, on the other hand, can be either quantised with a certain update rate or only derived according to SEW behaviours

Biologically inspired speaker verification

Speaker verification is an active research problem that has been addressed using a variety of different classification techniques. However, in general, methods inspired by the human auditory system tend to show better verification performance than other methods. In this thesis three biologically inspired speaker verification algorithms are presented

Arabic digits speech recognition and speaker identification in noisy environment using a hybrid model of VQ and GMM

This paper presents an automatic speaker identification and speech recognition for Arabic digits in noisy environment. In this work, the proposed system is able to identify the speaker after saving his voice in the database and adding noise. The mel frequency cepstral coefficients (MFCC) is the best approach used in building a program in the Matlab platform; also, the quantization is used for generating the codebooks. The Gaussian mixture modelling (GMM) algorithms are used to generate template, feature-matching purpose. In this paper, we have proposed a system based on MFCC-GMM and MFCC-VQ Approaches on the one hand and by using the Hybrid Approach MFCC-VQ-GMM on the other hand for speaker modeling. The White Gaussian noise is added to the clean speech at several signal-to-noise ratio (SNR) levels to test the system in a noisy environment. The proposed system gives good results in recognition rate

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

Advanced signal processing techniques for pitch synchronous sinusoidal speech coders

Recent trends in commercial and consumer demand have led to the increasing use of multimedia applications in mobile and Internet telephony. Although audio, video and data communications are becoming more prevalent, a major application is and will remain the transmission of speech. Speech coding techniques suited to these new trends must be developed, not only to provide high quality speech communication but also to minimise the required bandwidth for speech, so as to maximise that available for the new audio, video and data services. The majority of current speech coders employed in mobile and Internet applications employ a Code Excited Linear Prediction (CELP) model. These coders attempt to reproduce the input speech signal and can produce high quality synthetic speech at bit rates above 8 kbps. Sinusoidal speech coders tend to dominate at rates below 6 kbps but due to limitations in the sinusoidal speech coding model, their synthetic speech quality cannot be significantly improved even if their bit rate is increased. Recent developments have seen the emergence and application of Pitch Synchronous (PS) speech coding techniques to these coders in order to remove the limitations of the sinusoidal speech coding model. The aim of the research presented in this thesis is to investigate and eliminate the factors that limit the quality of the synthetic speech produced by PS sinusoidal coders. In order to achieve this innovative signal processing techniques have been developed. New parameter analysis and quantisation techniques have been produced which overcome many of the problems associated with applying PS techniques to sinusoidal coders. In sinusoidal based coders, two of the most important elements are the correct formulation of pitch and voicing values from the' input speech. The techniques introduced here have greatly improved these calculations resulting in a higher quality PS sinusoidal speech coder than was previously available. A new quantisation method which is able to reduce the distortion from quantising speech spectral information has also been developed. When these new techniques are utilised they effectively raise the synthetic speech quality of sinusoidal coders to a level comparable to that produced by CELP based schemes, making PS sinusoidal coders a promising alternative at low to medium bit rates.EThOS - Electronic Theses Online ServiceGBUnited Kingdo