8 citations · 15 across the 17 of their papers we have counts for
7 papers · 1 filter
End-to-end spoken language understanding using joint CTC loss and self-supervised, pretrained acoustic encoders
Jixuan Wang, Martin Radfar, Kai Wei +1
It is challenging to extract semantic meanings directly from audio signals in spoken language understanding (SLU), due to the lack of textual information. Popular end-to-end (E2E)…
Compute Cost Amortized Transformer for Streaming ASR
Yi Xie, Jonathan Macoskey, Martin Radfar +5
We present a streaming, Transformer-based end-to-end automatic speech recognition (ASR) architecture which achieves efficient neural inference through compute cost amortization. Ou…
A neural prosody encoder for end-ro-end dialogue act classification
Kai Wei, Dillon Knox, Martin Radfar +6
Dialogue act classification (DAC) is a critical task for spoken language understanding in dialogue systems. Prosodic features such as energy and pitch have been shown to be useful…
Multi-task RNN-T with Semantic Decoder for Streamable Spoken Language Understanding
Xuandi Fu, Feng-Ju Chang, Martin Radfar +4
End-to-end Spoken Language Understanding (E2E SLU) has attracted increasing interest due to its advantages of joint optimization and low latency when compared to traditionally casc…
Context-Aware Transformer Transducer for Speech Recognition
Feng-Ju Chang, Jing Liu, Martin Radfar +4
End-to-end (E2E) automatic speech recognition (ASR) systems often have difficulty recognizing uncommon words, that appear infrequently in the training data. One promising method, t…
FANS: Fusing ASR and NLU for on-device SLU
Martin Radfar, Athanasios Mouchtaris, Siegfried Kunzmann +1
Spoken language understanding (SLU) systems translate voice input commands to semantics which are encoded as an intent and pairs of slot tags and values. Most current SLU systems d…
End-to-End Neural Transformer Based Spoken Language Understanding
Martin Radfar, Athanasios Mouchtaris, Siegfried Kunzmann
Spoken language understanding (SLU) refers to the process of inferring the semantic information from audio signals. While the neural transformers consistently deliver the best perf…