Spectral Subtraction Based on Non-extensive Statistics for Speech Recognition
نویسندگان
چکیده
منابع مشابه
Feature normalization based on non-extensive statistics for speech recognition
Most compensation methods to improve the robustness of speech recognition systems in noisy environments such as spectral subtraction, CMN, and MVN, rely on the fact that noise and speech spectra are independent. However, the use of limited window in signal processing may introduce a cross-term between them, which deteriorates the speech recognition accuracy. To tackle this problem, we introduce...
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Statistical speech recognition is based on extensive statistics in which the additive property holds. On the other hand, it is well known that many complex systems, such as speech patterns, do not always have the additive property, and thus, do not follow extensive statistics. A framework of non-extensive statistics, proposed by Tsallis, can well represent the nonadditive characteristics of com...
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The weakness of conventional spectral subtractive-type algorithm is identified and presented in Section 2. The proposed remedial approach is described in Section 3. In Section 4, we show the proposed method’s effectiveness over conventional methods with representative experiments using Aurora 2. Concluding remarks are provided in Section 5. This paper addresses a novel noise-compensation scheme...
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This contribution presents and analyses an algorithm for the enhancement of noisy speech signals by means of spectral subtraction. In contrast to the standard spectral subtraction algorithm the proposed method does not need a speech activity detector nor histograms to learn signal statistics. The algorithm is capable to track non stationary noise signals and compares favorably with standard spe...
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Automatic speech recognition performance degrades significantly when speech is affected by environmental noise. Nowadays, the major challenge is to achieve good robustness in adverse noisy conditions so that automatic speech recognizers can be used in real situations. Spectral subtraction (SS) is a well-known and effective approach; it was originally designed for improving the quality of speech...
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ژورنال
عنوان ژورنال: IEICE Transactions on Information and Systems
سال: 2013
ISSN: 0916-8532,1745-1361
DOI: 10.1587/transinf.e96.d.1774