no code implementations • WS 2019 • Semih Yavuz, Abhinav Rastogi, Guan-Lin Chao, Dilek Hakkani-Tur
Recent advances in neural sequence-to-sequence models have led to promising results for several language generation-based tasks, including dialogue response generation, summarization, and machine translation.
no code implementations • WS 2019 • Guan-Lin Chao, Abhinav Rastogi, Semih Yavuz, Dilek Hakkani-Tür, Jindong Chen, Ian Lane
Understanding and conversing about dynamic scenes is one of the key capabilities of AI agents that navigate the environment and convey useful information to humans.
1 code implementation • 5 Jul 2019 • Guan-Lin Chao, Ian Lane
We focus on a specific condition, where the ontology is unknown to the state tracker, but the target slot value (except for none and dontcare), possibly unseen during training, can be found as word segment in the dialogue context.
no code implementations • 13 Jun 2019 • Guan-Lin Chao, William Chan, Ian Lane
Speech recognition in cocktail-party environments remains a significant challenge for state-of-the-art speech recognition systems, as it is extremely difficult to extract an acoustic signal of an individual speaker from a background of overlapping speech with similar frequency and temporal characteristics.
no code implementations • 12 Jul 2016 • Benjamin Elizalde, Guan-Lin Chao, Ming Zeng, Ian Lane
In particular, we present a method to compute and use semantic acoustic features to perform city-identification and the features show semantic evidence of the identification.