Attention-Based Dense LSTM for Speech Emotion Recognition
نویسندگان
چکیده
منابع مشابه
Speech Emotion Recognition Using Scalogram Based Deep Structure
Speech Emotion Recognition (SER) is an important part of speech-based Human-Computer Interface (HCI) applications. Previous SER methods rely on the extraction of features and training an appropriate classifier. However, most of those features can be affected by emotionally irrelevant factors such as gender, speaking styles and environment. Here, an SER method has been proposed based on a concat...
متن کاملAttention-Based LSTM with Multi-Task Learning for Distant Speech Recognition
Distant speech recognition is a highly challenging task due to background noise, reverberation, and speech overlap. Recently, there has been an increasing focus on attention mechanism. In this paper, we explore the attention mechanism embedded within the long short-term memory (LSTM) based acoustic model for large vocabulary distant speech recognition, trained using speech recorded from a singl...
متن کاملEnd-to-end attention-based distant speech recognition with Highway LSTM
End-to-end attention-based models have been shown to be competitive alternatives to conventional DNN-HMM models in the Speech Recognition Systems. In this paper, we extend existing end-to-end attentionbased models that can be applied for Distant Speech Recognition (DSR) task. Specifically, we propose an end-to-end attention-based speech recognizer with multichannel input that performs sequence ...
متن کاملAttention-Based Models for Speech Recognition
Recurrent sequence generators conditioned on input data through an attention mechanism have recently shown very good performance on a range of tasks including machine translation, handwriting synthesis [1, 2] and image caption generation [3]. We extend the attention-mechanism with features needed for speech recognition. We show that while an adaptation of the model used for machine translation ...
متن کاملSpeech Emotion Recognition Based on Power Normalized Cepstral Coefficients in Noisy Conditions
Automatic recognition of speech emotional states in noisy conditions has become an important research topic in the emotional speech recognition area, in recent years. This paper considers the recognition of emotional states via speech in real environments. For this task, we employ the power normalized cepstral coefficients (PNCC) in a speech emotion recognition system. We investigate its perfor...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEICE Transactions on Information and Systems
سال: 2019
ISSN: 0916-8532,1745-1361
DOI: 10.1587/transinf.2019edl8019