Search Results for author:
Found 14 papers, 3 papers with code
Phoneme-aware Encoding for Prefix-tree-based Contextual ASR
While the original TCPGen relies on grapheme-based encoding, we propose extending it with phoneme-aware encoding to better recognize words of unusual pronunciations.
UniverSLU: Universal Spoken Language Understanding for Diverse Tasks with Natural Language Instructions
Recent studies leverage large language models with multi-tasking capabilities, using natural language prompts to guide the model's behavior and surpassing performance of task-specific models.
Ranked #1 on
Spoken Language Understanding
on Fluent Speech Commands
(using extra training data)
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Decoder-only Architecture for Speech Recognition with CTC Prompts and Text Data Augmentation
Because the decoder architecture is the same as an autoregressive LM, it is simple to enhance the model by leveraging external text data with LM training.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Integration of Frame- and Label-synchronous Beam Search for Streaming Encoder-decoder Speech Recognition
Although frame-based models, such as CTC and transducers, have an affinity for streaming automatic speech recognition, their decoding uses no future knowledge, which could lead to incorrect pruning.
Integrating Pretrained ASR and LM to Perform Sequence Generation for Spoken Language Understanding
There has been an increased interest in the integration of pretrained speech recognition (ASR) and language models (LM) into the SLU framework.
Tensor decomposition for minimization of E2E SLU model toward on-device processing
We reduce the model size by applying tensor decomposition to the Conformer and E-Branchformer architectures used in our E2E SLU models.
A Study on the Integration of Pipeline and E2E SLU systems for Spoken Semantic Parsing toward STOP Quality Challenge
Recently there have been efforts to introduce new benchmark tasks for spoken language understanding (SLU), like semantic parsing.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
The Pipeline System of ASR and NLU with MLM-based Data Augmentation toward STOP Low-resource Challenge
In the track, we adopt a pipeline approach of ASR and NLU.
Joint Modelling of Spoken Language Understanding Tasks with Integrated Dialog History
Most human interactions occur in the form of spoken conversations where the semantic meaning of a given utterance depends on the context.
Streaming Joint Speech Recognition and Disfluency Detection
In this study, we propose Transformer-based encoder-decoder models that jointly solve speech recognition and disfluency detection, which work in a streaming manner.
Non-autoregressive Error Correction for CTC-based ASR with Phone-conditioned Masked LM
Connectionist temporal classification (CTC) -based models are attractive in automatic speech recognition (ASR) because of their non-autoregressive nature.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Distilling the Knowledge of BERT for CTC-based ASR
In this study, we propose to distill the knowledge of BERT for CTC-based ASR, extending our previous study for attention-based ASR.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
ASR Rescoring and Confidence Estimation with ELECTRA
We propose an ASR rescoring method for directly detecting errors with ELECTRA, which is originally a pre-training method for NLP tasks.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Distilling the Knowledge of BERT for Sequence-to-Sequence ASR
Experimental evaluations show that our method significantly improves the ASR performance from the seq2seq baseline on the Corpus of Spontaneous Japanese (CSJ).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
