speech recognition error rate
Word Error Rate Estimation for Speech Recognition: e WER
... automatic speech recognition (ASR) systems re- quires manually transcribed data in order to compute the word error rate (WER), which is often time-consuming and expen- ...character ...
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Using Chunk Based Partial Parsing of Spontaneous Speech in Unrestricted Domains for Reducing Word Error Rate in Speech Recognition
... Thus, the intuitive idea is to generate representations that allow for a discriminative judgment between different hypotheses in the Nbest list, so that eventually a more plausible candi[r] ...
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Generating Task Pertinent sorted Error Lists for Speech Recognition
... Word Error Rate (NE-WER), which consists of a normal WER restricted to the words of the reference present in a named entity ...entity recognition task, was ...entities recognition and in ...
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Performance Improvement in Keyword Spotting for Telephony Services
... those speech parts which have been similar to a keyword have not been rejected and have been kept to be checked afterwards, so false rejection rate has ...acceptance rate increases by decreasing the ...
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KT Speech Crawler: Automatic Dataset Construction for Speech Recognition from YouTube Videos
... language model and beam search significantly im- proves the performance on the test set of character- based end-to-end models (Hannun et al., 2014b), but as our goal was to demonstrate the impact of adding extracted ...
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Error Analysis and Improving Speech Recognition for Latvian Language
... Automatic Speech Recognition (ASR) system it is typical to evaluate system performance by calculating quantitative measures like accuracy, F1 score, Word Error Rate (WER) ...for ...
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An Efficient Isolated Speech Recognition Based on the Adaptive Rate Processing and Analysis
... The output of ASA is resampled uniformly. The extracted window parameters are employed to decide the resampling frequency [11-12].The resampler acts as a bridge between the non-uniform and the uniform signal processing ...
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Electromyographic analysis for silent speech detection
... automatic speech recognition ...EMG speech recognition system, in which a phone-based EMG speech with articulatory features and their relationship with signals of different channels are ...
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Using Chunk Based Partial Parsing of Spontaneous Speech in Unrestricted Domains for Reducing Word Error Rate in Speech Recognition
... Using Chunk Based Partial Parsing of Spontaneous Speech in Unrestricted Domains for Reducing Word Error Rate in Speech Recognition U s i n g C h u n k B a s e d P a r t i a l P a r s i n g o f S p o n[.] ...
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Driving ROVER with Segment based ASR Quality Estimation
... automatic speech recognition (ASR), the com- bination of transcription hypotheses produced by multiple systems usually leads to significant word error rate (WER) reductions compared to the ...
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Extracting Relationship of Meeting Minutes Generated by Speech Recognition System
... including error words caused by speech recognition, especially with the stopword elimination by TF- IDF, and with similarity calculation by the standard keyword extraction and the cosine similarity ...
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A Novel Approach for Software Requirement Specification
... of speech that has been degraded by noise [5], [6], [14]. The goal of speech enhancement varies according to the needs of specific applications, such as to increase the overall speech quality or ...
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Speech Recognition of Czech—Inclusion of Rare Words Helps
... continuous speech recognition of inflective languages, such as Czech, Russian or Serbo-Croatian, is heavily deteriorated by excessive out of vocabulary ...vocabulary rate we can achieve significant ...
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SPEAKER AUTHENTICATION USING ZERO CROSSING RATE WITH RESPECT TO BODO VOWEL PHONEME: A CLASSICAL EXPERIMENT
... universe. Speech is the most predominantly accepted, efficient and natural way for human beings to ...facilitate speech-enabled human computer interaction, in environments where users may experience ...
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Spontaneous Speech Effects In Large Vocabulary Speech Recognition Applications
... Spontaneous Speech Effects In Large Vocabulary Speech Recognition Applications Spontaneous Speech Effects In Large Vocabulary Speech Recognition Applications John Butzberger, Hy Murveit, Elizabeth Shr[.] ...
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Hmm dnn speech recognition techniques: a review
... Roman Serizel, Diego Giuliani[III]. In this paper DNN-HMM is used for children and adult’s speech recognition. Here two different corpuses are taken for training DNN in two ways. The first way is to train ...
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Study of Speech Recognition Technology and its significance in Human-Machine Interface
... to speech recognition. The first step in the processing is the speech analysis system, which provides an appropriate (spectral) representation of the characteristics of time-varying speech ...
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Review of Automatic Speech Recognition For Recognition of Speech and Speaker
... maximum likelihood estimator. Gaussian Mixture Model (GMM) is used to classify speech spurts into slow, medium and fast speech. The output likelihoods of these GMMs are used as input to a neural network ...
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Sign Language Recognition System with Speech Output
... Language Recognition Application Systems for Deaf-Mute People: A Review Based on Input-Process-Output, 2nd International Conference on Computer Science and Computational Intelligence 2017, ICCSCI 2017, Bali, ...
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Preprocessing Technique in Automatic Speech Recognition for Human Computer Interaction: An Overview
... on speech recognition is to use a close-talk ...generating speech utterance at normal communication level, the average signal to noise ratio (speech level) increase by about 3dB any time the ...
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