Enriching speech recognition with automatic detection of sentence boundaries and disfluencies

By Yang Liu, Elizabeth Shriberg, Andreas Stolcke, Dustin Hillard, Mari Ostendorf, Mary P. Harper. IEEE Transactions on Audio, Speech, and Language Processing, 2006

315 citations recorded by the source corpus.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/73e2df755908a4ebd801339717e25bf5f737244e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Shinji Watanabe
2. Mohit Bansal
3. Kevin Gimpel
4. Dong Yu
5. Jinyu Li
6. Karen Livescu
7. John Wieting
8. James R. Glass

Citations in the corpus

• Revisiting the Boundary between ASR and NLU in the Age of Conversational Dialog Systems (2021, background): “Although there is a long history of efforts to get ASR and NLU researchers to collaborate, for example, through conferences like HLT and DARPA programs (Liu et al. 2006; Ostendorf et al. 2008), the two communities are diverging again.”
• Parsing Speech: a Neural Approach to Integrating Lexical and Acoustic-Prosodic Information (2017, background): “Prosody is also known to provide useful cues to sentence boundaries (Liu et al., 2006), and automatic sentence segmentation performance has been shown to have a significant impact on parsing performance (Kahn and Ostendorf, 2012).”
• Low-Latency Real-Time Meeting Recognition and Understanding Using Distant Microphones and Omni-Directional Camera (2012, background): “Sentence boundaries are detected by estimating whether or not each word is a sentence head [46], [47].”