This paper describes recent improvements to an algorithm for identifying an unknown voice from a set of known voices using unconstrained speech material. These algorithms compare the underlying probability distributions of speech utterances using a method that is free of assumptions regarding the form of the distributions (e.g., Gaussian, etc.). In comparing two utterances, the algorithms accumulate minimum inter-frame distances between frames of the utterances. In recognition tests on the Switchboard database, using a closed population of speakers, we show that the new algorithm performs substantially better than the baseline algorithm. The modifications are segment-based scoring, limiting likelihood ratio estimates for robustness and estimating biases associated with reference files.>

The authors describe an algorithm for detecting the presence of speech from a particular individual, called the target, while rejecting speech from all other individuals. The algorithm requires samples of training data for the target speaker, as well as for a set of N other speakers, called reference speakers. These data are used to estimate the parameters of a set of speaker-pair discriminators. Each discriminator separates the target from one of the reference speakers, producing a positive or negative value for each input frame. The polarity of discriminators is such that positive output values favor the target. After the discriminator output has been integrated over a suitable time interval, the number of positive values is counted and compared with a detection threshold between 0 and N. In an experiment using clean speech material, 80% of targets were detected with only 2% of non-targets.>

Text-independent speaker recognition methods have been based on measurements of long-term statistics of individual speech frames. These methods are not capable of modeling speaker-dependent speech dynamics. In this paper, we describe a new method, based on template matching, that utilizes temporal information to advantage. The template-matching method performs text-dependent recognition as a special case. Performance of the template-matching method is compared with that of similar recently-developed methods.

The error rates typically reported for connected speech recognition (CSR) and keyword recognition (KWR) differ by at least an order of magnitude. We present a simple new KWR method and use the new method to investigate the factors that are responsible for this large apparent "performance gap". The new KWR method concatenates templates to match all the input speech, and can utilize knowledge about the vocabulary and syntax of the input speech. We present performance results for systems that differ in the following factors: syntax, speaker training, and template vocabulary. The results suggest that template-concatenation KWR methods can give good results for unrestricted input speech.

This paper presents the development, study, and experimental results of a narrowband speech coder called Harmonic Deviations (HDV) Vocoder. The HDV coder is based on the LPC vocoder, and it transmits additional information over and above the data transmitted by the LPC vocoder, in the form of deviations between the speech spectrum and the LPC all-pole model spectrum at a selected set of frequencies. At the receiver, the spectral deviations are used to generate the excitation signal for the all-pole synthesis filter. The paper describes and compares several methods for extracting the spectral deviations from the speech signal and for encoding them. To limit the bit-rate of the HDV coder to 2.4 kb/s the paper discusses several methods including orthogonal transformation and minimum-mean-square-error scalar quantization of log area ratios, two-stage vector-scalar quantization, and variable frame rate transmission. The paper also presents the results of speech-quality optimization of the HDV coder at 2.4 kb/s. Both noisefree and noisy channel applications are considered. The resulting HDV coders yield noticeable improvement in speech quality over LPC vocoders.

This paper describes the design of a baseband LPC coder that transmits speech over 9.6 kbit/s (kilobit/second) synchronous channels with random bit errors of up to 1 percent. Presented are the results of our investigation of a number of aspects of the baseband LPC coder with the goal of maximizing the quality of the transmitted speech. Important among these aspects are: bandwidth of the baseband, coding of the baseband residual, high-frequency regeneration, and error protection of important transmission parameters. The paper discusses these and other issues, presents the results of speech-quality tests conducted during the various stages of optimization, and describes the details of the optimized speech coder. This optimized speech coding algorithm has been implemented as a real-time full-duplex system on an array processor. Informal listening tests of the real-time coder have shown that the coder produces good speech quality in the absence of channel bit errors and introduces only a slight degradation in quality for channel bit error rates of up to 1 percent.

This paper presents the results of our optimization study of 16 kb/s APC coders operating over noisy channels. With the objective of achieving good speech quality and a robust coder performance for channel bit-error rates of up to 1%, we have investigated a number of issues including: the tradeoff between voice-data bandwidth and error-protection bandwidth; the amount of error protection for individual transmission parameters; comparison of several residual coding methods; the relative performance of the two ways of sequencing the spectral and pitch predictors; use of folded binary code for encoding the quantized residual; and smoothing of the decoded residual. Most impressive of the several interesting and useful results reported in the paper is that the final optimized, robust coder design yields speech quality that degrades only slightly as the bit-error rate is increased from 0% to 1%.

This paper presents the results of our investigation of the various aspects of baseband LPC coders with the goal of maximizing the speech quality at a transmission bit-rate of 9.6 kb/s and for channel bit-error rates of up to 1%. Important among these aspects are: baseband width, coding of baseband, high-frequency regeneration, and error protection of important transmission parameters. The paper discusses these and other issues, presents the results of speech-quality tests conducted during the various stages of optimization, and describes the details of the optimized speech coder.

This paper considers the optimization of speech quality of adaptive predictive coding (APC) systems for transmission over a synchronous 16 kb/s channel. Among the important issues included in this on-going optimization study are: comparative evaluation of several methods for adaptive coding of the APC residual; comparative testing of several methods for adaptive shaping of the spectrum of the quantization noise; and optimization of various parameter values and their bit allocation. In addition to reporting the results from this study, we report on the occurrence of "limit cycles" or regions of excessive quantization noise build-up, offer an explanation for their cause in terms of the feedback gain (or "loop gain") of the APC transmitter, and present experimental results obtained using several remedial means for this problem. Also, we report on the relative properties of different APC coder configurations. Based on the results of our optimization study to date, we present several optimized APC systems.