Results 1 to 10 of about 1,028,836 (338)
THE RECOGNITION OF SPEECH BY MACHINE [PDF]
, 1961 "May 1, 1961." "Based on a thesis submitted to the Department of Electrical Engineering, M. I. T. ... 1959, in partial fulfillment of the requirements for the degree of Doctor of Science." "May 1, 1961."
George W. Hughes
openalex +4 more sources
International Journal of Networked and Distributed Computing (IJNDC), 2021 This study compared and analyzed the speech recognition performance of Korean phonological rules for cloud-based Open APIs, and analyzed the speech recognition characteristics of Korean phonological rules.
Hyun Jae Yoo +3 more
doaj +1 more source
The effect of speech pathology on automatic speaker verification: a large-scale study
Scientific Reports, 2023 Navigating the challenges of data-driven speech processing, one of the primary hurdles is accessing reliable pathological speech data. While public datasets appear to offer solutions, they come with inherent risks of potential unintended exposure of ...
Soroosh Tayebi Arasteh +5 more
doaj +1 more source
A Deep Learning Method Using Gender-Specific Features for Emotion Recognition
Sensors, 2023 Speech reflects people’s mental state and using a microphone sensor is a potential method for human–computer interaction. Speech recognition using this sensor is conducive to the diagnosis of mental illnesses.
Li-Min Zhang +5 more
doaj +1 more source
Speech Recognition with No Speech or with Noisy Speech [PDF]
ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019 The performance of automatic speech recognition systems(ASR) degrades in the presence of noisy speech. This paper demonstrates that using electroencephalography (EEG) can help automatic speech recognition systems overcome performance loss in the presence of noise.
Gautam Krishna +3 more
openaire +3 more sources
Band importance for speech-in-speech recognition [PDF]
JASA Express Letters, 2021 Predicting masked speech perception typically relies on estimates of the spectral distribution of cues supporting recognition. Current methods for estimating band importance for speech-in-noise use filtered stimuli. These methods are not appropriate for speech-in-speech because filtering can modify stimulus features affecting auditory stream ...
Adam K. Bosen, Emily Buss
openaire +3 more sources
A Hybrid Speech Enhancement Algorithm for Voice Assistance Application
Sensors, 2021 In recent years, speech recognition technology has become a more common notion. Speech quality and intelligibility are critical for the convenience and accuracy of information transmission in speech recognition.
Jenifa Gnanamanickam +2 more
doaj +1 more source
Implicit learning and individual differences in speech recognition: an exploratory study
Frontiers in Psychology, 2023 Individual differences in speech recognition in challenging listening environments are pronounced. Studies suggest that implicit learning is one variable that may contribute to this variability. Here, we explored the unique contributions of three indices
Ranin Khayr, Hanin Karawani, Karen Banai
doaj +1 more source
, 2021 AbstractSpeech recognition can be formulated as the problem of guessing a sequence of words that produces a sequence of sounds. The human brain is remarkably good at solving this problem, even though the same words correspond to many different sounds, because of accents or characteristics of the voice. Moreover, the environment is always noisy, to that
openaire +4 more sources
Frontier Research on Low-Resource Speech Recognition Technology
Sensors, 2023 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,
Wushour Slam, Yanan Li, Nurmamet Urouvas
doaj +1 more source