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Found 10 papers, 1 papers with code
An Efficient Self-Learning Framework For Interactive Spoken Dialog Systems
Dialog systems, such as voice assistants, are expected to engage with users in complex, evolving conversations.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Task Oriented Dialogue as a Catalyst for Self-Supervised Automatic Speech Recognition
We demonstrate that our CLC family of approaches can improve the performance of ASR models on OD3, a new public large-scale semi-synthetic meta-dataset of audio task-oriented dialogues, by up to 19. 2%.
Using External Off-Policy Speech-To-Text Mappings in Contextual End-To-End Automated Speech Recognition
Despite improvements to the generalization performance of automated speech recognition (ASR) models, specializing ASR models for downstream tasks remains a challenging task, primarily due to reduced data availability (necessitating increased data collection), and rapidly shifting data distributions (requiring more frequent model fine-tuning).
Multi-Modal Pre-Training for Automated Speech Recognition
Traditionally, research in automated speech recognition has focused on local-first encoding of audio representations to predict the spoken phonemes in an utterance.
Low-Resource Adaptation of Open-Domain Generative Chatbots
Recent work building open-domain chatbots has demonstrated that increasing model size improves performance.
DiPCo -- Dinner Party Corpus
We present a speech data corpus that simulates a "dinner party" scenario taking place in an everyday home environment.
End-to-end Anchored Speech Recognition
The anchored segment refers to the wake-up word part of an audio stream, which contains valuable speaker information that can be used to suppress interfering speech and background noise.
Improving noise robustness of automatic speech recognition via parallel data and teacher-student learning
For real-world speech recognition applications, noise robustness is still a challenge.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
LSTM-based Whisper Detection
We prove that, with enough data, the LSTM model is indeed as capable of learning whisper characteristics from LFBE features alone compared to a simpler MLP model that uses both LFBE and features engineered for separating whisper and normal speech.
Device-directed Utterance Detection
In this work, we propose a classifier for distinguishing device-directed queries from background speech in the context of interactions with voice assistants.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
