#### Filter Results:

- Full text PDF available (116)

#### Publication Year

1981

2017

- This year (5)
- Last 5 years (47)
- Last 10 years (125)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Data Set Used

#### Key Phrases

#### Method

Learn More

- Lawrence R. Rabiner, Biing-Hwang Juang
- Prentice Hall signal processing series
- 1993

- Biing-Hwang Juang, Wu Hou, Chin-Hui Lee
- IEEE Trans. Speech and Audio Processing
- 1997

A critical component in the pattern matching approach to speech recognition is the training algorithm, which aims at producing typical (reference) patterns or models for accurate pattern comparison. In this paper, we discuss the issue of speech recognizer training from a broad perspective with root in the classical Bayes decision theory. We differentiate… (More)

- Frank K. Soong, Biing-Hwang Juang
- ICASSP
- 1984

Line Spectrum Pair (LSP) was first introduced by Itakura [1,21 as an alternative LPC spectral representations. It was found that this new representation has such interesting properties as (I) all zeros of LSP polynomials are on the unit circle, (2) the corresponding zeros of the symmetric and anti-symmetric LSP polynomials are interlaced, and (3) the… (More)

Recently, due to the advent of artificial neural networks and learning vector quantizers, there is a resurgent interest in reexamining the classical techniques of discriminant analysis to suit the new classifier structures. One of the particular problems of interest is minimum error classification in which the misclassification probability is to be… (More)

- Chin-Hui Lee, Chih-Heng Lin, Biing-Hwang Juang
- IEEE Trans. Signal Processing
- 1991

It is generally agreed that, for a given speech recognition task, a speaker-dependent system usually outperforms a speaker-independent system, as long as a sufficient amount of training data is available. When the amount of speaker-specific training data is limited, however, such a performance gain is not guaranteed. One way to improve the performance is to… (More)

- Biing-Hwang Juang, Lawrence R. Rabiner
- IEEE Trans. Acoustics, Speech, and Signal…
- 1990

- Biing-Hwang Juang, Shigeru Katagiri
- IEEE Trans. Signal Processing
- 1992

- Biing-Hwang Juang, Augustine H. Gray
- ICASSP
- 1982

- Biing-Hwang Juang, Lawrence R. Rabiner
- IEEE Trans. Acoustics, Speech, and Signal…
- 1985

In this paper a signal modeling technique based upon finite mixture autoregressive probabilistic functions of Markov chains is developed and applied to the problem of speech recognition, particularly speaker-independent recognition of isolated digits. Two types of mixture probability densities are investigated: finite mixtures of Gaussian autoregressive… (More)

- Tomohiro Nakatani, Takuya Yoshioka, Keisuke Kinoshita, Masato Miyoshi, Biing-Hwang Juang
- IEEE Transactions on Audio, Speech, and Language…
- 2010

This paper proposes a statistical model-based speech dereverberation approach that can cancel the late reverberation of a reverberant speech signal captured by distant microphones without prior knowledge of the room impulse responses. With this approach, the generative model of the captured signal is composed of a source process, which is assumed to be a… (More)