Results 31 to 40 of about 35,015 (307)
Automatic speech recognition and speech variability: A review
Speech Communication, 2007 Major progress is being recorded regularly on both the technology and exploitation of automatic speech recognition (ASR) and spoken language systems. However, there are still technological barriers to flexible solutions and user satisfaction under some circumstances.
Mohamed Benzeghiba +12 more
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Band-pass filtering of the time sequences of spectral parameters for robust wireless speech recognition [PDF]
, 2006 In this paper we address the problem of automatic speech recognition when wireless speech communication systems are involved. In this context, three main sources of distortion should be considered: acoustic environment, speech coding and transmission ...
Peláez-Moreno, Carmen +11 more
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Lexicon adaptation for subword speech recognition
, 2022 S.562-567In this paper we present two approaches to adapt a syllable-based recognition lexicon in an Automatic Speech Recognition (ASR) setting. The motivation is to evaluate whether adaptation techniques commonly used on a word level can also be ...
Svendsen, T. +3 more
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Exploring discrete wavelet transforms for bimodal speech recognition [PDF]
Serbian Journal of Electrical EngineeringDiscrete Wavelet Transforms (DWTs) provide time–frequency representations that are well suited for nonstationary signals such as speech. This study presents a comparison of four wavelet families (Daubechies, Symlets, Coiflets, and Biorthogonal) for ...
Marković Branko +2 more
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Information, 2023 Superficially, read and spontaneous speech—the two main kinds of training data for automatic speech recognition—appear as complementary, but are equal: pairs of texts and acoustic signals. Yet, spontaneous speech is typically harder for recognition. This
Philipp Gabler +3 more
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Trajectory Clustering For Automatic Speech Recognition [PDF]
, 2005 4 p.
Han, Y., Veth, J.M. de, Boves, L.W.J.
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Recognizing Voice Over IP: A Robust Front-End for Speech Recognition on the World Wide Web [PDF]
, 2001 The Internet Protocol (IP) environment poses two relevant sources of distortion to the speech recognition problem: lossy speech coding and packet loss. In this paper, we propose a new front-end for speech recognition over IP networks.
Peláez-Moreno, Carmen +5 more
core +1 more source
Integrating morphology into automatic speech recognition
2009 IEEE Workshop on Automatic Speech Recognition & Understanding, 2009 This paper proposes a novel approach to integrate the morphology as a model into an automatic speech recognition (ASR) system for morphologically rich languages. The high out-of-vocabulary (OOV) word rates have been a major challenge for ASR in morphologically productive languages.
Hasim Sak +2 more
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automatic speech recognition [PDF]
, 2011 Automatic speech recognition (ASR) systems convert speech from a recorded audio signal to text. Humans convert words to speech with their speech production mechanism. An ASR system aims to infer those original words given the observable signal. The most common and as of today best method is the probabilistic approach. A speech signal corresponds to any
Rainer E. Gruhn +2 more
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Automatic Speech Recognition from Neural Signals: A Focused Review
Frontiers in Neuroscience, 2016 Speech interfaces have become widely accepted and are nowadays integrated in various real-life applications and devices. They have become a part of our daily life. However, speech interfaces presume the ability to produce intelligible speech, which might
Christian Herff, Tanja Schultz
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