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Found 7 papers, 2 papers with code
Evaluating User Perception of Speech Recognition System Quality with Semantic Distance Metric
Measuring automatic speech recognition (ASR) system quality is critical for creating user-satisfying voice-driven applications.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Span Pointer Networks for Non-Autoregressive Task-Oriented Semantic Parsing
An effective recipe for building seq2seq, non-autoregressive, task-oriented parsers to map utterances to semantic frames proceeds in three steps: encoding an utterance $x$, predicting a frame's length |y|, and decoding a |y|-sized frame with utterance and ontology tokens.
Semantic Distance: A New Metric for ASR Performance Analysis Towards Spoken Language Understanding
We define SemDist as the distance between a reference and hypothesis pair in a sentence-level embedding space.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+14
El Volumen Louder Por Favor: Code-switching in Task-oriented Semantic Parsing
Being able to parse code-switched (CS) utterances, such as Spanish+English or Hindi+English, is essential to democratize task-oriented semantic parsing systems for certain locales.
MTOP: A Comprehensive Multilingual Task-Oriented Semantic Parsing Benchmark
Scaling semantic parsing models for task-oriented dialog systems to new languages is often expensive and time-consuming due to the lack of available datasets.
Likelihood Ratios and Generative Classifiers for Unsupervised Out-of-Domain Detection In Task Oriented Dialog
We are hitherto the first to investigate the use of generative classifiers for OOD detection at test-time.
PyText: A Seamless Path from NLP research to production
We introduce PyText - a deep learning based NLP modeling framework built on PyTorch.
