Titlebook: Statistical Language and Speech Processing; 7th International Co Carlos Martín-Vide,Matthew Purver,Senja Pollak Conference proceedings 2019

不知疲倦

A Speech Test Set of Practice Business Presentations with Additional Relevant Textsvocabulary and named entities is benefitable. The corpus consists of 39 presentations in English, each up to 90 s long. The speakers are high school students from European countries with English as their second language. We benchmark three baseline ASR systems on the corpus and show their imperfection.

Vsd168

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证实

The Time-Course of Phoneme Category Adaptation in Deep Neural Networksxical information. In previous work, we have shown that deep neural network-based (DNN) ASR systems can learn to adapt their phoneme category boundaries from a few labeled examples after exposure (i.e., training) to ambiguous sounds, as humans have been found to do. Here, we investigate the time-cou

不透气

Towards Pragmatic Understanding of Conversational Intent: A Multimodal Annotation Approach to Multipd gestures. The outlined research stems from the ‘growth point theory’ and ‘integrated systems hypothesis’, which proposes that co-speech gestures (including hand gestures, facial expressions, posture, and gazing) and speech originate from the same representation, but are not necessarily based solel

忧伤

Lilia, A Showcase for Fast Bootstrap of Conversation-Like Dialogues Based on a Goal-Oriented Systema probable sentence based on the user’s statement along with a partial view of the dialogue history. While appealing to some extent, these approaches require huge training sets of general-purpose data and lack a principled way to intertwine language generation with information retrieval from back-en

正面

Recent Advances in End-to-End Spoken Language Understanding signal by means of a single end-to-end neural network model. Two SLU tasks are considered: named entity recognition (NER) and semantic slot filling (SF). For these tasks, in order to improve the model performance, we explore various techniques including speaker adaptation, a modification of the con

right-atrium

A Study on Multilingual Transfer Learning in Neural Machine Translation: Finding the Balance Betweeng algorithm, requires to make several choices such as selecting the training data and more particularly language pairs and their available quantity and quality. Other important choices must be made during the preprocessing step, like selecting data to learn subword units, the subsequent model’s voca

专心

A Deep Learning Approach to Self-expansion of Abbreviations Based on Morphology and Context Distance abbreviations and introduce a corpus-based method for their expansion. The method divides the processing into three key stages: abbreviation identification, full form candidate extraction, and abbreviation disambiguation. First, potential abbreviations are identified by combining pattern matching a

Canopy