Introduction With the continuous advancement of artificial intelligence technology, the AI’s abilities to “hear” and “see” are becoming increasingly powerful. From speech recognition to image recognition, AI can not only interact with us through sound but also understand and analyze the surrounding world through vision. These technologies have not only changed the way we interact … Read more
Selected from arXiv Authors: Anuroop Sriram et al. Translated by Machine Heart Contributors: Li Yazhou, Li Zenan Baidu recently published a paper proposing the use of Generative Adversarial Networks (GAN) to achieve a robust speech recognition system. The authors state that the new framework does not rely on the domain-specific knowledge or simplified assumptions often … Read more
Recently, Alibaba algorithm expert Kun Cheng participated in the ICASSP 2017 conference with the paper titled Improving Latency-Controlled BLSTM Acoustic Models for Online Speech Recognition. Author Kun Cheng communicating with attendees The research of this paper is based on the premise that to achieve better speech recognition accuracy, the Latency-controlled BLSTM model was used in … Read more
With the popularization of artificial intelligence, speech has become an important interaction method, especially since Baidu’s speech recognition and wake-up technology was launched, it has attracted widespread attention from developers. On August 6, at the 65th “Analysis and Practice of Baidu Speech Recognition and Wake-Up Technology” salon jointly held by Baidu Developer Center and InfoQ, … Read more
Excerpt from Awni Translation by Machine Heart Contributors:Nurhachu Null,Lu Xue Since the application of deep learning in the field of speech recognition, the word error rate has significantly decreased. However, speech recognition has not yet reached human-level performance and still faces multiple unresolved issues. This article discusses various aspects of the unresolved problems in speech … Read more