What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Linguistics
- Speech recognition
Speech recognition, Artificial intelligence, Natural language processing, Speech corpus and Acoustic model are her primary areas of study.
Lori Lamel frequently studies issues relating to Phone and Speech recognition.
She combines subjects such as Word recognition, Context, Machine learning and Vocabulary with her study of Artificial intelligence.
Her work on Language model and Language identification as part of general Natural language processing research is frequently linked to SIGNAL, bridging the gap between disciplines.
Her Speech corpus research is multidisciplinary, incorporating elements of Acoustic phonetics and Reading.
Her TIMIT research includes themes of NIST and Utterance.
Her most cited work include:
- Darpa Timit Acoustic-Phonetic Continuous Speech Corpus CD-ROM {TIMIT} | NIST (693 citations)
- DARPA TIMIT:: acoustic-phonetic continuous speech corpus CD-ROM, NIST speech disc 1-1.1 (674 citations)
- TIMIT Acoustic-Phonetic Continuous Speech Corpus (417 citations)
What are the main themes of her work throughout her whole career to date?
Lori Lamel mostly deals with Speech recognition, Artificial intelligence, Natural language processing, Language model and Word error rate.
Her Speech recognition study incorporates themes from Word and Phone.
The study incorporates disciplines such as Transcription, Context and Vocabulary in addition to Artificial intelligence.
Her study in Natural language processing is interdisciplinary in nature, drawing from both Pronunciation, Linguistics and Mandarin Chinese.
Her Language model research is multidisciplinary, relying on both NIST, Artificial neural network, Text corpus and Word recognition.
Her Word error rate study combines topics from a wide range of disciplines, such as Decoding methods, Conversation and Speech processing.
She most often published in these fields:
- Speech recognition (64.84%)
- Artificial intelligence (61.72%)
- Natural language processing (55.08%)
What were the highlights of her more recent work (between 2012-2020)?
- Speech recognition (64.84%)
- Artificial intelligence (61.72%)
- Natural language processing (55.08%)
In recent papers she was focusing on the following fields of study:
Lori Lamel mainly investigates Speech recognition, Artificial intelligence, Natural language processing, Linguistics and Language model.
Her work carried out in the field of Speech recognition brings together such families of science as Annotation and Mandarin Chinese.
Her Artificial intelligence study integrates concerns from other disciplines, such as Context, Realization and Pattern recognition.
The concepts of her Natural language processing study are interwoven with issues in Transcription, Word and Vocabulary.
In her study, which falls under the umbrella issue of Language model, Cepstrum and Multilayer perceptron is strongly linked to Transcription.
She interconnects Arabic and Duration in the investigation of issues within Speech corpus.
Between 2012 and 2020, her most popular works were:
- TIMIT Acoustic-Phonetic Continuous Speech Corpus (417 citations)
- Score normalization and system combination for improved keyword spotting (87 citations)
- Comparing decoding strategies for subword-based keyword spotting in low-resourced languages. (24 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Linguistics
- Speech recognition
Her primary areas of investigation include Artificial intelligence, Natural language processing, Speech recognition, Keyword spotting and Transcription.
She has researched Artificial intelligence in several fields, including Arabic and Code-switching.
The various areas that she examines in her Natural language processing study include Variety, Prosody and Selection.
In general Speech recognition study, her work on Speech processing often relates to the realm of Maximization, thereby connecting several areas of interest.
Her biological study spans a wide range of topics, including Bantu languages, Speech corpus, Phonetics and Sound quality.
Lori Lamel has included themes like American English, Utterance, TIMIT and Reading in her Speech corpus study.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
