ASR Error Management for Improving Spoken Language Understanding
暂无分享,去创建一个
Renato De Mori | Yannick Estève | Nathalie Camelin | Sahar Ghannay | Edwin Simonnet | R. Mori | Y. Estève | Sahar Ghannay | Nathalie Camelin | E. Simonnet
[1] Jonathan G. Fiscus,et al. A post-processing system to yield reduced word error rates: Recognizer Output Voting Error Reduction (ROVER) , 1997, 1997 IEEE Workshop on Automatic Speech Recognition and Understanding Proceedings.
[2] Guillaume Gravier,et al. Corpus description of the ESTER Evaluation Campaign for the Rich Transcription of French Broadcast News , 2004, LREC.
[3] Atsunori Ogawa,et al. ASR error detection and recognition rate estimation using deep bidirectional recurrent neural networks , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[4] Martine Adda-Decker,et al. Combining Continuous Word Representation and Prosodic Features for ASR Error Prediction , 2015, SLSP.
[5] Alexander I. Rudnicky,et al. Investigations on ensemble based semi-supervised acoustic model training , 2005, INTERSPEECH.
[6] Daniel Povey,et al. The Kaldi Speech Recognition Toolkit , 2011 .
[7] Alexis Nasr,et al. MACAON : Une chaîne linguistique pour le traitement de graphes de mots , 2009 .
[8] Bowen Zhou,et al. Dependency-based Convolutional Neural Networks for Sentence Embedding , 2015, ACL.
[9] Gökhan Tür,et al. Syntax or semantics? knowledge-guided joint semantic frame parsing , 2016, 2016 IEEE Spoken Language Technology Workshop (SLT).
[10] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[11] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[12] Yannick Estève,et al. Word embeddings combination and neural networks for robustness in ASR error detection , 2015, 2015 23rd European Signal Processing Conference (EUSIPCO).
[13] Benoît Favre,et al. Word Embedding Evaluation and Combination , 2016, LREC.
[14] Paul Deléglise,et al. Exploring the use of Attention-Based Recurrent Neural Networks For Spoken Language Understanding , 2015, NIPS 2015.
[15] Paul Deléglise,et al. Acoustic Word Embeddings for ASR Error Detection , 2016, INTERSPEECH.
[16] Olivier Galibert,et al. The ETAPE corpus for the evaluation of speech-based TV content processing in the French language , 2012, LREC.
[17] Geoffrey Zweig,et al. Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding , 2015, IEEE/ACM Transactions on Audio, Speech, and Language Processing.
[18] Mark Steedman,et al. Transforming Dependency Structures to Logical Forms for Semantic Parsing , 2016, TACL.
[19] François Yvon,et al. Practical Very Large Scale CRFs , 2010, ACL.
[20] Sophie Rosset,et al. Semantic annotation of the French media dialog corpus , 2005, INTERSPEECH.
[21] Gökhan Tür,et al. Multi-Domain Joint Semantic Frame Parsing Using Bi-Directional RNN-LSTM , 2016, INTERSPEECH.
[22] George R. Doddington,et al. The ATIS Spoken Language Systems Pilot Corpus , 1990, HLT.
[23] Guillaume Gravier,et al. The ester 2 evaluation campaign for the rich transcription of French radio broadcasts , 2009, INTERSPEECH.
[24] L. Deng,et al. Calibration of Confidence Measures in Speech Recognition , 2011, IEEE Transactions on Audio, Speech, and Language Processing.
[25] Guillaume Gravier,et al. Is it time to Switch to word embedding and recurrent neural networks for spoken language understanding? , 2015, INTERSPEECH.
[26] Paul Deléglise,et al. LIUM and CRIM ASR System Combination for the REPERE Evaluation Campaign , 2014, TSD.
[27] Gokhan Tur,et al. Spoken Language Understanding: Systems for Extracting Semantic Information from Speech , 2011 .
[28] Andreas Stolcke,et al. Finding consensus in speech recognition: word error minimization and other applications of confusion networks , 2000, Comput. Speech Lang..
[29] Hermann Ney,et al. Comparing Stochastic Approaches to Spoken Language Understanding in Multiple Languages , 2011, IEEE Transactions on Audio, Speech, and Language Processing.