In speech coding, segment vocoders offer good intelligibility at low bit rates. A segment vocoder has four basic components 1)Segmentation of input speech 2)Segment quantization 3)Residual quantization 4)Synthesis of speech. Most segment vocoders use a recognition approach to segment quantization. In this paper, we assume a different approach to segment quantization. The segmental unit is a syllable and the segment codebook stores the sequence of LPC vectors. During the encoding process the speech segment is quantized using the sequence of LPC vectors that result in the smallest residual energy. PESQ scores indicate that this vocoder achieves better quality compared to that of a corresponding vocoder that uses a speech recognition framework. ©2010 IEEE.

Hema Murthy

Department of Computer Science and Engineering

Veezhinathan Kamakoti

Abhijit Pradhan

Sadhana Chevireddy

Bit rates

Codebooks

ENCODING PROCESS

Low Bit Rate

MINIMUM RESIDUAL ENERGY

RESIDUAL ENERGY

Speech segments

Speech coding

Speech intelligibility

Synthesis (chemical)

Vocoders

Speech Recognition

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

A low-bit rate segment vocoder using minimum residual energy criteria

Proceedings of 16th National Conference on Communications, NCC 2010

In the development of a syllable-centric automatic speech recognition (ASR) system, segmentation of the acoustic signal into syllabic units is an important stage. Although the short-term energy (STE) function contains useful information about syllable segment boundaries, it has to be processed before segment boundaries can be extracted. This paper presents a subband-based group delay approach to segment spontaneous speech into syllable-like units. This technique exploits the additive property of the Fourier transform phase and the deconvolution property of the cepstrum to smooth the STE function of the speech signal and make it suitable for syllable boundary detection. By treating the STE function as a magnitude spectrum of an arbitrary signal, a minimum-phase group delay function is derived. This group delay function is found to be a better representative of the STE function for syllable boundary detection. Although the group delay function derived from the STE function of the speech signal contains segment boundaries, the boundaries are difficult to determine in the context of long silences, semivowels, and fricatives. 'In this paper, these issues are specifically addressed and algorithms are developed to improve the segmentation performance. The speech signal is first passed through a bank of three filters, corresponding to three different spectral bands. The STE functions of these signals are computed. Using these three STE functions, three minimum-phase group delay functions are derived. By combining the evidence derived from these group delay functions, the syllable boundaries are detected. Further, a multiresolutionbased technique is presented to overcome the problem of shift in segment boundaries during smoothing. Experiments carried out on the Switchboard and OGI-MLTS corpora show that the error in segmentation is at most 25 milliseconds for 67% and 76.6% of the syllable segments, respectively. © 2004 Hindawi Publishing Corporation.

Fulltext

Eurasip Journal on Applied Signal Processing

Subband-based group delay segmentation of spontaneous speech Into syllable-like units

Electronics Letters

Very low bit rate speech coding using a diphone-based recognition and synthesis approach

IEEE Transactions on Speech and Audio Processing

A mixed excitation LPC vocoder model for low bit rate speech coding

IEEE Transactions on Acoustics, Speech, and Signal Processing

LPC speech coding based on variable-length segment quantization

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221)

Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs

Journal	Data powered by TypesetProceedings of 16th National Conference on Communications, NCC 2010
Publisher	Data powered by TypesetIEEE
Open Access	No