Matrix quantization and mixed excitation based linear predictive speech coding at very low bit rates

Date

2003-10

Author

Özaydın, Selma
Baykal, Buyurman

Metadata

Show full item record

Item Usage Stats

239
views

0
downloads

A matrix quantization scheme and a very low bit rate vocoder is developed to obtain good quality speech for low capacity communication links. The new matrix quantization method operates at bit rates between 400 and 800 bps and using a 25 ms linear predictive coding (LPC) analysis frame, spectral distortion about 1 dB is achieved at 800 bps. Techniques for improving the performance at very low bit rate vocoding include quantization of residual line spectral frequency (LSF) vectors, multistage matrix quantization, joint quantization of pitch and voiced/unvoiced/mixed decisions and a technique to obtain voiced/unvoiced/mixed decisions. In the new matrix quantization based mixed excitation (MQME) vocoder, the residual LSF vectors for two consecutive frames are obtained using autoregressive moving average (ARMA) prediction, then grouped into a superframe and jointly quantized. For other speech parameters, quantization is made in each frame. The residual LSF vector quantization yields bit rate reduction in the vocoder. For the MQME vocoder, listening tests have proven that an efficient and high quality coding has been achieved at a bit rate of 1200 bps. Test results are compared with the mixed excitation based 2400 bps MELP vocoder which is chosen as the new federal standard, and it is observed that the degradation in speech quality is tolerable and the performance is near the 2400 bps MELP vocoder particularly in quiet environments.

Subject Keywords

Very low bit rate, LSF matrix quantization, LSF vector quantization, Mixed excitation

URI

https://hdl.handle.net/11511/28352

Journal

Speech Communication

DOI

https://doi.org/10.1016/s0167-6393(03)00009-8

Collections

Department of Electrical and Electronics Engineering, Article

Suggestions

OpenMETU
Core

Error exponents for variable-length block codes with feedback and cost constraints Nakiboğlu, Barış (Institute of Electrical and Electronics Engineers (IEEE), 2008-03-01) Variable-length block-coding schemes are investigated for discrete memoryless channels with ideal feedback under cost constraints. Upper and lower bounds are found for the minimum achievable probability of decoding error P-e,P-min as a function of constraints R, P, and T on the transmission rate, average cost, and average block length, respectively. For given R and P, the lower and upper bounds to the exponent -(In P-e,P-min)/(T) over bar are asymptotically equal as (T) over bar -> infinity. The resulting r...
Cmos LNA design for system-on-chip receiver stages Telli, A; Askar, M (2004-09-10) In this study, narrowband single-ended inductive source degenerated Low Noise Amplifiers (LNAs) for "System-on-Chip" receiver stages have been designed, simulated and compared using Mietec CMOS 0.7 mu m process and the Cadence/BSIM3v3 tool with active or L-biased DC-bias circuitries. Since there is an intension to use LNAs for GSM and S-band low earth orbit (LEO) space applications, the operating frequencies have been chosen as 900MHz, 2025 MHz and 2210 MHz.
Wireless speech recognition using fixed point mixed excitation linear prediction (MELP) vocoder Acar, D; Karci, MH; Ilk, HG; Demirekler, Mübeccel (2002-07-19) A bit stream based front-end for wireless speech recognition system that operates on fixed point mixed excitation linear prediction (MELP) vocoder is presented in this paper. Speaker dependent, isolated word recognition accuracies obtained from conventional and bit stream based front-end systems are obtained and their statistical significance is discussed. Feature parameters are extracted from original (wireline) and decoded speech (conventional) and from the quantized spectral information (bit stream) of t...
Approximate Bayesian Smoothing with Unknown Process and Measurement Noise Covariances Ardeshiri, Tohid; Özkan, Emre; Orguner, Umut; Gustafsson, Fredrik (2015-12-01) We present an adaptive smoother for linear state-space models with unknown process and measurement noise covariances. The proposed method utilizes the variational Bayes technique to perform approximate inference. The resulting smoother is computationally efficient, easy to implement, and can be applied to high dimensional linear systems. The performance of the algorithm is illustrated on a target tracking example.
Graph-based joint channel estimation and data detection for large-scale multiuser MIMO-OFDM systems / Tekin, Şeref Yaşar; Yılmaz, Ali Özgür; Department of Electrical and Electronics Engineering (2015) In this thesis, a graph-based soft iterative receiver for large-scale multiuser MIMO-OFDM systems is proposed that performs joint channel estimation and data detection over time-varying frequency selective channel. In an uplink scenario, factor graph structures for the transmitter of users and the receiver of base-station are presented, which provide Gaussian message passing between nodes. Instead of LLR, reliability information of symbols are used to decrease complexity of the proposed algorithm. Training ...

Citation Formats

S. Özaydın and B. Baykal, “Matrix quantization and mixed excitation based linear predictive speech coding at very low bit rates,” Speech Communication, pp. 381–392, 2003, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/28352.