What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Speech recognition
- Machine learning
Tanja Schultz mostly deals with Speech recognition, Artificial intelligence, Natural language processing, Word error rate and Speech processing.
Her Speech recognition study frequently intersects with other fields, such as Vocabulary.
Her studies deal with areas such as Computer vision and Pattern recognition as well as Artificial intelligence.
She has researched Natural language processing in several fields, including Turkish, Adaptation and German.
Her Word error rate research focuses on subjects like Discriminative model, which are linked to Cache language model and International Phonetic Alphabet.
Her work carried out in the field of Speech processing brings together such families of science as Field, Speech production and Speech synthesis.
Her most cited work include:
- Language-independent and language-adaptive acoustic modeling for speech recognition (327 citations)
- Language-independent and language-adaptive acoustic modeling for speech recognition (327 citations)
- Silent speech interfaces (287 citations)
What are the main themes of her work throughout her whole career to date?
Tanja Schultz mainly focuses on Speech recognition, Artificial intelligence, Natural language processing, Word error rate and Speech processing.
She combines topics linked to Vocabulary with her work on Speech recognition.
Her work deals with themes such as Computer vision and Pattern recognition, which intersect with Artificial intelligence.
Her study in Natural language processing is interdisciplinary in nature, drawing from both Pronunciation, Word and German.
Her study involves Voice activity detection and Silent speech interface, a branch of Speech processing.
The study incorporates disciplines such as Set and Cache language model in addition to Language model.
She most often published in these fields:
- Speech recognition (61.87%)
- Artificial intelligence (49.77%)
- Natural language processing (30.82%)
What were the highlights of her more recent work (between 2015-2021)?
- Speech recognition (61.87%)
- Human–computer interaction (9.13%)
- Artificial intelligence (49.77%)
In recent papers she was focusing on the following fields of study:
The scientist’s investigation covers issues in Speech recognition, Human–computer interaction, Artificial intelligence, Dementia and Speech production.
The various areas that she examines in her Speech recognition study include Artificial neural network, Brain–computer interface and Convolutional neural network.
Her Human–computer interaction research integrates issues from Field, Biosignal, Task, Task analysis and Eye tracking.
Tanja Schultz focuses mostly in the field of Artificial intelligence, narrowing it down to topics relating to Natural language processing and, in certain cases, Word.
Her Dementia research includes elements of Feature extraction, Cognition and Gerontology.
Her Speech synthesis study combines topics in areas such as Natural and Speech processing.
Between 2015 and 2021, her most popular works were:
- Biosignal-Based Spoken Communication: A Survey (74 citations)
- Speech synthesis from ECoG using densely connected 3D convolutional neural networks (49 citations)
- Automatic Speech Recognition from Neural Signals: A Focused Review. (49 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Speech recognition
- Machine learning
Tanja Schultz focuses on Speech recognition, Electroencephalography, Dementia, Speech production and Artificial intelligence.
Her Speech recognition research incorporates themes from Feature extraction, Brain–computer interface and Convolutional neural network.
Her Electroencephalography study integrates concerns from other disciplines, such as State, Selection and Computer vision.
Her Speech production research is multidisciplinary, incorporating perspectives in Biosignal, Human–computer interaction and Speech synthesis.
Her Artificial intelligence research incorporates elements of Human memory and Natural language processing.
Her Natural language processing research includes themes of Feature selection, Automatic speech processing, Predictive text and Dementia screening.
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