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Multistage vector quantization (MSVQ) is a technique for low complexity implementation of high-dimensional quantizers, which has found applications within speech, audio, and image coding. In this paper, a mult...
Variability of speaker accent is a challenge for effective human communication as well as speech technology including automatic speech recognition and accent identification. The motivation of this study is to ...
A noise suppression algorithm is proposed based on filtering the spectrotemporal modulations of noisy signals. The modulations are estimated from a multiscale representation of the signal spectrogram generated...
We describe two voice-to-phoneme conversion algorithms for speaker-independent voice-tag creation specifically targeted at applications on embedded platforms. These algorithms (batch mode and sequential) are comp...
This paper experimentally shows the importance of perceptual continuity of the expressive strength in vocal timbre for natural change in vocal expression. In order to synthesize various and continuous expressi...
Many modern speech bandwidth extension techniques predict the high-frequency band based on features extracted from the lower band. While this method works for certain types of speech, problems arise when the c...
Wide band digital audio signals have a very high data-rate associated with them due to their complex nature and demand for high-quality reproduction. Although recent technological advancements have significant...
This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function. Problems in analyzing voiced speech using linear ...
Recent research on the TIMIT corpus suggests that longer-length acoustic models are more appropriate for pronunciation variation modelling than the context-dependent phones that conventional automatic speech r...
When applying automatic speech recognition (ASR) to meeting recordings including spontaneous speech, the performance of ASR is greatly reduced by the overlap of speech events. In this paper, a method of separa...
We describe an FFT-based companding algorithm for preprocessing speech before recognition. The algorithm mimics tone-to-tone suppression and masking in the auditory system to improve automatic speech recogniti...
Dereverberation is required in various speech processing applications such as handsfree telephony and voice-controlled systems, especially when signals are applied that are recorded in a moderately or highly r...
In various adaptive estimation applications, such as acoustic echo cancellation within teleconferencing systems, the input signal is a highly correlated speech. This, in general, leads to extremely slow conver...
We investigate novel algorithms to improve the convergence and reduce the complexity of time-domain convolutive blind source separation (BSS) algorithms. First, we propose MMax partial update time-domain convo...
A sparse system identification algorithm for network echo cancellation is presented. This new approach exploits both the fast convergence of the improved proportionate normalized least mean square (IPNLMS) alg...
The μ-law proportionate normalized least mean square (MPNLMS) algorithm has been proposed recently to solve the slow convergence problem of the proportionate normalized least mean square (PNLMS) algorithm afte...
This paper proposes an audio-visual speech recognition method using lip information extracted from side-face images as an attempt to increase noise robustness in mobile environments. Our proposed method assume...
This paper introduces new algorithms for the blind separation of audio sources using modal decomposition. Indeed, audio signals and, in particular, musical signals can be well approximated by a sum of damped s...
An acoustic echo cancellation structure with a single loudspeaker and multiple microphones is, from a system identification perspective, generally modelled as a single-input multiple-output system. Such a syst...
We introduce an efficient hidden Markov model-based voice activity detection (VAD) algorithm with time-variant state-transition probabilities in the underlying Markov chain. The transition probabilities vary i...
Proportionate adaptive filters can improve the convergence speed for the identification of sparse systems as compared to their conventional counterparts. In this paper, the idea of proportionate adaptation is ...
The paper provides an analysis of the transient and the steady-state behavior of a filtered-x partial-error affine projection algorithm suitable for multichannel active noise control. The analysis relies on energ...
This paper investigates the significance of combining cepstral features derived from the modified group delay function and from the short-time spectral magnitude like the MFCC. The conventional group delay fun...
This paper derives an upper bound for the step size of the sequential partial update (PU) LMS adaptive algorithm when the input signal is a periodic reference consisting of several harmonics. The maximum step ...
We present a new technique for separating two speech signals from a single recording. The proposed method bridges the gap between underdetermined blind source separation techniques and those techniques that model...
Animated agents are becoming increasingly frequent in research and applications in speech science. An important challenge is to evaluate the effectiveness of the agent in terms of the intelligibility of its vi...
This paper presents a new method to detect speech/nonspeech components of a given noisy signal. Employing the combination of binary Walsh basis functions and an analysis-synthesis scheme, the original noisy sp...
Learn more about the impact the EURASIP Journal on Audio, Speech, and Music Processing has worldwide
Speed
50 days to first decision for all manuscripts
75 days to first decision for reviewed manuscripts only
222 days from submission to acceptance
34 days from acceptance to publication
Citation Impact
1.558 - 2-year Impact Factor
2.008 - 5-year Impact Factor
1.101 - Source Normalized Impact per Paper (SNIP)
0.259 - SCImago Journal Rank (SJR)
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