Tag Archives: Speech Processing

Information Retrieval Machine Learning Publications Speech Processing Speech Recognition

HMM-based ASR

ASR is a system whose purpose is to convert speech into text. Several types of ASR have been designed by speech processing researchers, however those based on the HMM algorithm are the most accurate. Here, we will focus on the principle of HMM.

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Publications Speech Processing

Blind Audio Source Separation

Blind Audio Source Separation (BASS) is a crucial problem in the field of speech and audio processing. Its goal is to separate different sources from their mixture. In the case of audio mining, trying to analyze the content of the audio signal generally consists of designing a print or pattern of a given sound to recognize. Thus, one has to admit that when the signal is a mixture, it becomes difficult to extract suitable features allowing the design of a particular sound.

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Publications Speech Processing

Noise Reduction

Noise Reduction is an important preprocessing step in any speech processing system. In so far as in speech recognition, acoustic models are generally obtained from clean speech signals, it must be recognized that preprocessing aims to clean a speech signal. We present here two of the most popular techniques: spectral subtraction and Wiener filter.

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