Improving Speech Recognition Using a Data-Driven Approach
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Automatic speech recognition (ASR) systems, trained on speech signals from close-talking microphones, generally fail in recognizing far-field speech. In this paper, we present a Hilbert Envelope based feature extraction technique to alleviate the artifacts ...
Automatic speech recognition (ASR) systems, trained on speech signals from close-talking microphones, generally fail in recognizing far-field speech. In this paper, we present a Hilbert Envelope based feature extraction technique to alleviate the artifacts ...
We describe the design of Kaldi, a free, open-source toolkit for speech recognition research. Kaldi provides a speech recognition system based on finite-state transducers (using the freely available OpenFst), together with detailed documentation and script ...
Real world applications such as hands-free dialling in cars may have to perform recognition of spoken digits in potentially very noisy environments. Existing state-of-the-art solutions to this problem use feature-based Hidden Markov Models~(HMMs), with a p ...
Although research has previously been done on multilingual speech recognition, it has been found to be very difficult to improve over separately trained systems. The usual approach has been to use some kind of “universal phone set” that covers multiple lan ...
Performance of a typical automatic speech recognition (ASR) system severely degrades when it encounters speech from reverberant environments. Part of the reason for this degradation is the feature extraction techniques that use analysis windows which are m ...
Performance of a typical automatic speech recognition (ASR) system severely degrades when it encounters speech from reverberant environments. Part of the reason for this degradation is the feature extraction techniques that use analysis windows which are m ...
Real world applications such as hands-free dialling in cars may have to perform recognition of spoken digits in potentially very noisy environments. Existing state-of-the-art solutions to this problem use feature-based Hidden Markov Models (HMMs), with a p ...
Real world applications such as hands-free dialling in cars may have to perform recognition of spoken digits in potentially very noisy environments. Existing state-of-the-art solutions to this problem use feature-based Hidden Markov Models (HMMs), with a p ...
This paper proposes a Distant Speech Recognition system based on a novel speaker Localization and Beamforming (SRLB) algorithm. To localize the speaker an algorithm based on Steered Response Power by utilizing harmonic structures of speech signal is propos ...
