منابع مشابه
Look, Listen and Learn - A Multimodal LSTM for Speaker Identification
Speaker identification refers to the task of localizing the face of a person who has the same identity as the ongoing voice in a video. This task not only requires collective perception over both visual and auditory signals, the robustness to handle severe quality degradations and unconstrained content variations are also indispensable. In this paper, we describe a novel multimodal Long Short-T...
متن کاملITR: Listen and Learn – Artificial Intelligence in Auditory Environments
Most academic departments in computer science and electrical engineering provide some sort of intellectual umbrella to integrate research in machine learning, computer vision, robotics, and artificial intelligence (AI). For largely historical and outmoded reasons, however, research in auditory computation and machine listening has not been included in these efforts. We hope to rectify this situ...
متن کاملListen and learn: engaging young people, their families and schools in early intervention research
Recent policy guidelines highlight the importance of increasing the identification of young people at risk of developing mental health problems in order to prevent their transition to long-term problems, avoid crisis and remove the need for care through specialist mental health services or hospitalisation. Early awareness of the often insidious behavioural and cognitive changes associated with ...
متن کاملListen, Learn, Like! Dorsolateral Prefrontal Cortex Involved in the Mere Exposure Effect in Music
We used functional magnetic resonance imaging to investigate the neural basis of the mere exposure effect in music listening, which links previous exposure to liking. Prior to scanning, participants underwent a learning phase, where exposure to melodies was systematically varied. During scanning, participants rated liking for each melody and, later, their recognition of them. Participants showe...
متن کاملListen, Attend and Spell
We present Listen, Attend and Spell (LAS), a neural network that learns to transcribe speech utterances to characters. Unlike traditional DNN-HMM models, this model learns all the components of a speech recognizer jointly. Our system has two components: a listener and a speller. The listener is a pyramidal recurrent network encoder that accepts filter bank spectra as inputs. The speller is an a...
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ژورنال
عنوان ژورنال: Nature
سال: 2003
ISSN: 0028-0836,1476-4687
DOI: 10.1038/425768a