Combining continuous word representation and prosodic features for ASR error prediction

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9449, Issue , 2015, Pages 84-95

  Ghannay, Sahar ^a   Estève, Yannick ^a   Camelin, Nathalie ^a   Dutrey, Camille ^b   Santiago, Fabian ^b   Adda Decker, Martine ^b  

^a UNIVERSITÉ DU MAINE   (France)

^b UNIVERSITÉ SORBONNE NOUVELLE PARIS 3   (France)

Author keywords

ASR error detection; Continuous word representations; Neural networks; Prosodic features

Indexed keywords

COMPUTATIONAL LINGUISTICS; ERRORS; NATURAL LANGUAGE PROCESSING SYSTEMS; NETWORK ARCHITECTURE; NEURAL NETWORKS; SPEECH PROCESSING;

AUTOMATIC SPEECH RECOGNITION; AUTOMATIC TRANSCRIPTION; COMBINATION APPROACHES; CONDITIONAL RANDOM FIELD; NATURAL LANGUAGE PROCESSING; PROSODIC FEATURES; STATE-OF-THE-ART APPROACH; WORD REPRESENTATIONS;

SPEECH RECOGNITION;

EID: 84952310974     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-25789-1_9     Document Type: Conference Paper

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