Table of Contents

• Sequence Tagging Models

  • The role of disfluencies in topic classification of human-human conversations.
  • Robust cross-domain disfluency detection with pattern match networks. - 1811-07236.html?view=bibtex) [[code]](https://github.com/vickyzayats/disfluency_detection)
  • Joint prediction of punctuation and disfluency in speech transcripts. - speech.org/archive/Interspeech_2020/abstracts/1277.html)
  • Disfluency detection using auto-correlational neural networks. - 1490.bib) [[code]](https://github.com/pariajm/deep-disfluency-detector)
  • Robust cross-domain disfluency detection with pattern match networks. - 1811-07236.html?view=bibtex) [[code]](https://github.com/vickyzayats/disfluency_detection)
  • Disfluency detection using a bidirectional LSTM.
  • Multi-domain disfluency and repair detection.
  • A Sequential Repetition Model for Improved Disfluency Detection.
  • The role of disfluencies in topic classification of human-human conversations.

• Others

  • The role of disfluencies in topic classification of human-human conversations.
  • Speech disfluencies occur at higher perplexities. - 1.11.bib)
  • Controllable time-delay transformer for real-time punctuation prediction and disfluency detection.
  • Expectation and locality effects in the prediction of disfluent fillers and repairs in English speech. - 3015.bib)
  • Disfluencies and human speech transcription errors. - speech.org/archive/Interspeech_2019/abstracts/3134.html) [[data]](https://github.com/vickyzayats/switchboard_corrected_reannotated)
  • Unediting: detecting disfluencies without careful transcripts. - 1161.bib)
  • The role of disfluencies in topic classification of human-human conversations.
  • Preliminaries to a theory of speech disfluencies.
  • Disfluent Speech Segments Detection and Remediation.
  • Analysis of Disfluency in Children’s Speech. - speech.org/archive/Interspeech_2020/abstracts/3037.html)

• Data Augmenatation Techniques

  • Disfluency detection with unlabeled data and small BERT models.
  • Auxiliary sequence labeling tasks for disfluency detection.
  • Disfluency detection with unlabeled data and small BERT models.
  • Planning and generating natural and diverse disfluent texts as augmentation for disfluency detection. - main.113.bib) [[code]](https://github.com/GT-SALT/Disfluency-Generation-and-Detection/tree/main/disfluency-detection)
  • Combining self-training and self-supervised learning for unsupervised disfluency detection. - main.142.bib) [[code]](https://github.com/scir-zywang/self-training-self-supervised-disfluency)
  • Auxiliary sequence labeling tasks for disfluency detection.
  • Multi-task self-supervised learning for disfluency detection.
  • Improving disfluency detection by self-training a self-attentive model. - main.346.bib) [[code]](https://github.com/pariajm/joint-disfluency-detector-and-parser) [[data]](https://github.com/pariajm/english-fisher-annotations)
  • Semi-supervised disfluency detection. - 1299.bib)
  • Noisy BiLSTM-based models for disfluency detection. - speech.org/archive/Interspeech_2019/abstracts/1336.html)

• Noisy Channel Models

  • Disfluency detection using a noisy channel model and a deep neural language model. - 2087.bib)
  • The impact of language models and loss functions on repair disfluency detection. - 1071.bib)
  • An improved model for recognizing disfluencies in conversational speech.
  • A TAG-based noisy channel model of speech repair. - 1005.bib)

• Translation Based Models

  • Adapting translation models for transcript disfluency detection.
  • A neural attention model for disfluency detection. - 1027.bib)

• Parsing Based Models

  • Semantic parsing of disfluent speech.
  • Neural constituency parsing of speech transcripts. - 1282.bib) [[code]](https://github.com/pariajm/joint-disfluency-detector-and-parser/tree/naacl2019)
  • Transition-based disfluency detection using LSTMs. - 1296.bib) [[code]](https://github.com/hitwsl/transition_disfluency)
  • Joint transition-based dependency parsing and disfluency detection for automatic speech recognition texts. - 1109.bib)
  • Joint parsing and disfluency detection in linear time. - 1013.bib)
  • Edit detection and parsing for transcribed speech. - 1016.bib)

• Incremental Disfluency Detection

  • Re-framing incremental deep language models for dialogue processing with multi-task learning. - main.43.bib) [[code]](https://github.com/mortezaro/mtl-disfluency-detection)
  • Recurrent neural networks for incremental disfluency detection. - 1011.bib)
  • Joint incremental disfluency detection and dependency parsing. - 1011.bib)

• E2E Speech Recognition and Disfluency Removal

  • Improved robustness to disfluencies in RNN-Transducer based speech recognition. - 2012-06259.html?view=bibtex)
  • End-to-end speech recognition and disfluency removal. - emnlp.186.bib) [[code]](https://github.com/pariajm/e2e-asr-and-disfluency-removal-evaluator)

• E2E Speech Translation and Disfluency Removal

  • NAIST’s machine translation systems for IWSLT 2020 conversational speech translation task. - 1.21.bib)
  • Generating fluent translations from disfluent text without access to fluent references: IIT Bombay@IWSLT2020. - 1.22.bib)
  • Fluent translations from disfluent speech in end-to-end speech translation. - 1285.bib) [[data]](https://github.com/isl-mt/fluent-fisher)
  • Segmentation and disfluency removal for conversational speech translation. - us/research/publication/segmentation-and-disfluency-removal-for-conversational-speech-translation/bibtex/)

• Using Acoustic/Prosodic Cues

  • Giving attention to the unexpected: using prosody innovations in disfluency detection. - 1008.bib) [[code]](https://github.com/vickyzayats/disfluency_detection)
  • Parsing speech: a neural approach to integrating lexical and acoustic-prosodic information. - 1007.bib) [[code]](https://github.com/shtoshni92/speech_parsing)
  • On the role of style in parsing speech with neural models. - the-Role-of-Style-in-Parsing-Speech-with-Neural-Tran-Yuan/6658f850d2d7d4fa899bf2c8da93fc5ef1bd00b6) [[code]](https://github.com/trangham283/prosody_nlp/tree/master/code/self_attn_speech_parser)
  • Disfluency detection based on speech-aware token-by-token sequence labeling with BLSTM-CRFs and attention mechanisms.
  • Automatic punctuation and disfluency detection in multi-party meetings using prosodic and lexical cues. - speech.org/archive/icslp_2002/i02_0949.html)
  • Automatic disfluency identification in conversational speech using multiple knowledge sources. - disfluency-identification-in-speech-using-Liu-Shriberg/d772b10d1a5ee70ee1daa9dccc66243a917c1b73)