Results 191 to 200 of about 19,864 (256)

A cross-dataset study on automatic detection of autism spectrum disorder from text data. [PDF]

Acta Psychiatr Scand
Wawer A, Chojnicka I, Sarzyńska-Wawer J, Krawczyk M.   +3 more
europepmc   +1 more source

Offensive language detection in low resource languages: A use case of Persian language. [PDF]

PLoS One
Mozafari M, Mnassri K, Farahbakhsh R, Crespi N.   +3 more
europepmc   +1 more source

Respiratory Diseases Diagnosis Using Audio Analysis and Artificial Intelligence: A Systematic Review. [PDF]

Sensors (Basel)
Kapetanidis P, Kalioras F, Tsakonas C, Tzamalis P, Kontogiannis G, Karamanidou T, Stavropoulos TG, Nikoletseas S.   +7 more
europepmc   +1 more source

Code-mixing unveiled: Enhancing the hate speech detection in Arabic dialect tweets using machine learning models. [PDF]

PLoS One
Alhazmi A, Mahmud R, Idris N, Mohamed Abo ME, Eke CI.   +4 more
europepmc   +1 more source

The inner portrait: What does reflexivity in qualitative health professions education research look like?

Anatomical Sciences Education, EarlyView.
Gabrielle Brand, Steve Wise, Michelle D. Lazarus   +2 more
wiley   +1 more source

Query-by-example Spoken Term Detection For OOV terms

2009 IEEE Workshop on Automatic Speech Recognition & Understanding, 2009
The goal of Spoken Term Detection (STD) technology is to allow open vocabulary search over large collections of speech content. In this paper, we address cases where search term(s) of interest (queries) are acoustic examples. This is provided either by identifying a region of interest in a speech stream or by speaking the query term.
Carolina Parada, Abhinav Sethy, Bhuvana Ramabhadran   +2 more
openalex   +2 more sources

A comparison of query-by-example methods for spoken term detection

Interspeech 2009, 2009
Abstract : In this paper we examine an alternative interface for phonetic search, namely query-by-example, that avoids OOV issues associated with both standard word-based and phonetic search methods. We develop three methods that compare query lattices derived from example audio against a standard ngrambased phonetic index and we analyze factors ...
Wade Shen, Christopher White, Timothy J. Hazen   +2 more
openalex   +3 more sources

An acoustic segment modeling approach to query-by-example spoken term detection

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012
The framework of posteriorgram-based template matching has been shown to be successful for query-by-example spoken term detection (STD). This framework employs a tokenizer to convert query examples and test utterances into frame-level posteriorgrams, and applies dynamic time warping to match the query posteriorgrams with test posteriorgrams to locate ...
Haipeng Wang, Cheung-Chi Leung, Tan Lee, Bin Ma, Haizhou Li   +4 more
openalex   +3 more sources

Query-by-example spoken term detection using bessel features

2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES), 2015
In this paper, a new set of features for addressing the problem of unsupervised query-by-example spoken term detection is proposed. The main purpose of this is to find a spoken query in large speech databases. In unsupervised audio search, language specific resources are not required.
Drisya Vasudev, Suryakanth V. Gangashetty, Kancharagunta Kishan Babu, K S Riyas   +3 more
openalex   +3 more sources