AIMC Topic: Speech Recognition Software

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Automated Generation of Clinical Reports Using Sensing Technologies with Deep Learning Techniques.

Sensors (Basel, Switzerland)
This study presents a pioneering approach that leverages advanced sensing technologies and data processing techniques to enhance the process of clinical documentation generation during medical consultations. By employing sophisticated sensors to capt...

Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic model.

Journal of affective disorders
BACKGROUND: Prior research has associated spoken language use with depression, yet studies often involve small or non-clinical samples and face challenges in the manual transcription of speech. This paper aimed to automatically identify depression-re...

A Speech Recognition Method Based on Domain-Specific Datasets and Confidence Decision Networks.

Sensors (Basel, Switzerland)
This paper proposes a speech recognition method based on a domain-specific language speech network (DSL-Net) and a confidence decision network (CD-Net). The method involves automatically training a domain-specific dataset, using pre-trained model par...

Design of Political Online Teaching Based on Artificial Speech Recognition and Deep Learning.

Computational intelligence and neuroscience
With the emergence of the information age, computers have entered the homes of ordinary people and have become essential daily appliances for people. The integration of people and computers has become more popular and in-depth. Based on this situatio...

Deep learning applications in telerehabilitation speech therapy scenarios.

Computers in biology and medicine
Nowadays, many application scenarios benefit from automatic speech recognition (ASR) technology. Within the field of speech therapy, in some cases ASR is exploited in the treatment of dysarthria with the aim of supporting articulation output. However...

End-to-End Lip-Reading Open Cloud-Based Speech Architecture.

Sensors (Basel, Switzerland)
Deep learning technology has encouraged research on noise-robust automatic speech recognition (ASR). The combination of cloud computing technologies and artificial intelligence has significantly improved the performance of open cloud-based speech rec...

Concurrent Associative Memories With Synaptic Delays.

IEEE transactions on neural networks and learning systems
This article presents concurrent associative memories with synaptic delays useful for processing sequences of real vectors. Associative memories with synaptic delays were introduced by the authors for symbolic sequential inputs and demonstrated sever...

An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation.

Nature communications
We propose a Double EXponential Adaptive Threshold (DEXAT) neuron model that improves the performance of neuromorphic Recurrent Spiking Neural Networks (RSNNs) by providing faster convergence, higher accuracy and a flexible long short-term memory. We...

Artificial Intelligence Can Improve Patient Management at the Time of a Pandemic: The Role of Voice Technology.

Journal of medical Internet research
Artificial intelligence-driven voice technology deployed on mobile phones and smart speakers has the potential to improve patient management and organizational workflow. Voice chatbots have been already implemented in health care-leveraging innovativ...

Streaming cascade-based speech translation leveraged by a direct segmentation model.

Neural networks : the official journal of the International Neural Network Society
The cascade approach to Speech Translation (ST) is based on a pipeline that concatenates an Automatic Speech Recognition (ASR) system followed by a Machine Translation (MT) system. Nowadays, state-of-the-art ST systems are populated with deep neural ...