21 papers · ranked by Valyu relevance
Wushour Slam, Yanan Li, Nurmamet Urouvas, Alessandro Artusi
With the development of continuous speech recognition technology, users have put forward higher requirements in terms of speech recognition accuracy. Low-resource speech recognition, as a typical speech recognition technology under restricted conditions, has become a research hotspot nowadays because of its low…
Vlado Delić, Zoran Perić, Milan Sečujski, Nikša Jakovljević + 5 more
'Jelena Nikolić' 'Dragiša Mišković' 'Nikola Simić' 'Siniša Suzić' 'Tijana Delić'] Speech technologies have been developed for decades as a typical signal processing area, while the last decade has brought a huge progress based on new machine learning paradigms. Owing not only to their intrinsic complexity but also to…
Wookey Lee, Jessica Jiwon Seong, Busra Ozlu, Bong Sup Shim + 4 more
Voice is one of the essential mechanisms for communicating and expressing one’s intentions as a human being. There are several causes of voice inability, including disease, accident, vocal abuse, medical surgery, ageing, and environmental pollution, and the risk of voice loss continues to increase. Novel approaches…
Urmila Shrawankar, Anjali Mahajan
Along with the rapid development of information technology, the amount of information generated at a given time far exceeds human's ability to organize, search, and manipulate without the help of automatic systems. Now a days so many tools and techniques are available for storage and retrieval of information. User uses…
R. Sandanalakshmi, P. Abinaya Viji, M. Kiruthiga, M. Manjari + 1 more
'M. Sharina'] An efficient speech to text converter for mobile application is presented in this work. The prime motive is to formulate a system which would give optimum performance in terms of complexity, accuracy, delay and memory requirements for mobile environment. The speech to text converter consists of two stages…
Ataklti Kahsu, Solomon Teferra
This thesis proposes and describes a research attempt at designing and developing a speakerindependent spontaneous automatic speech recognition system for Tigrigna. The acoustic model of the Speech Recognition System is developed using Carnegie Mellon University's Automatic Speech Recognition development tool (Sphinx)…
Urmila Shrawankar, V. M. Thakare
Whenever we think of cyber applications, we visualize the model that gives the idea that we are sitting in front of computer at home or workplace connected to internet and performing all the work that generally we have to go and do on a specific place for example e-shopping, ebanking, e-education etc.
Karl J. Friston, Noor Sajid, David Ricardo Quiroga-Martinez, Thomas Parr + 2 more
This paper introduces active listening, as a unified framework for synthesising and recognising speech. The notion of active listening inherits from active inference, which considers perception and action under one universal imperative: to maximise the evidence for our (generative) models of the world. First, we…
Sachin Lakra, T. V. Prasad, Deepak Kumar Sharma, Shree Harsh Atrey + 1 more
'Anubhav Sharma'] Abstract - For the past few decades, man has been trying to create an intelligent computer which can talk and respond like he can. The task of creating a system that can talk like a human being is the primary objective of Automatic Speech Recognition. Various Speech Recognition techniques have been…
Cai Wingfield, Li Su, Xunying Liu, Chao Zhang + 4 more
There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiological process, is an important case in point. Automatic Speech…
Gulmira Bekmanova, Banu Yergesh, Altynbek Sharipbay, Assel Mukanova + 4 more
'Valentina Franzoni' 'Giulio Biondi' 'Alfredo Milani' 'Jordi Vallverdú'] The emotional speech recognition method presented in this article was applied to recognize the emotions of students during online exams in distance learning due to COVID-19. The purpose of this method is to recognize emotions in spoken speech…
Rachit Shukla
Automatic Speech Recognition (ASR) is the interdisciplinary subfield of computational linguistics that develops methodologies and technologies that enables the recognition and translation of spoken language into text by computers. It incorporates knowledge and research in linguistics, computer science, and electrical…
Oli Danyi Liu, Hao Tang, Naomi H. Feldman, Sharon Goldwater
Speech representations in the human brain do not simply mirror the instantaneous speech signal; rather, they display several properties that are hypothesized to facilitate the integration of speech sounds into words. In particular, neural encodings of speech maintain information that has dissipated from the acoustics…
Jinghan Wu, Yakun Zhang, Liang Xie, Ye Yan + 5 more
'Xingwei An' 'Erwei Yin' 'Dong Ming'] Silent speech recognition breaks the limitations of automatic speech recognition when acoustic signals cannot be produced or captured clearly, but still has a long way to go before being ready for any real-life applications. To address this issue, we propose a novel silent speech…
Lotte Weerts, Claudia Clopath, Dan F. M. Goodman
Automatic speech recognition (ASR) software has been suggested as a candidate model of the human auditory system thanks to dramatic improvements in performance in recent years. To test this hypothesis, we compared several state-of-the-art ASR systems to results from humans on a barrage of standard psychoacoustic…
Juraj Kacur, Boris Puterka, Jarmila Pavlovicova, Milos Oravec + 1 more
'Iren E. Kuznetsova'] There are many speech and audio processing applications and their number is growing. They may cover a wide range of tasks, each having different requirements on the processed speech or audio signals and, therefore, indirectly, on the audio sensors as well. This article reports on tests and…
Ismail Shahin
Speaker identification performance is almost perfect in neutral talking environments; however, the performance is deteriorated significantly in shouted talking environments. This work is devoted to proposing, implementing and evaluating new models called Second-Order Circular Suprasegmental Hidden Markov Models…
Thomas Hueber, Eric Tatulli, Laurent Girin, Jean-luc Schwartz
Sensory processing is increasingly conceived in a predictive framework in which neurons would constantly process the error signal resulting from the comparison of expected and observed stimuli. Surprisingly, few data exist on the amount of predictions that can be computed in real sensory scenes. Here, we focus on the…
Dorota Kamińska
This article presents the novel method for emotion recognition from speech based on committee of classifiers. Different classification methods were juxtaposed in order to compare several alternative approaches for final voting. The research is conducted on three different types of Polish emotional speech: acted out…
Gopala K. Anumanchipalli, Josh Chartier, Edward F. Chang
The ability to read out, or decode, mental content from brain activity has significant practical and scientific implications^1^. For example, technology that translates cortical activity into speech would be transformative for people unable to communicate as a result of neurological impairment^2,3,4^. Decoding speech…
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This research presents a novel approach to obstacle detection during navigation using a combination of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The primary objective is to generate accurate image captions that describe the content of images, which is crucial for applications such…