# Speech Recognition and Synthesis

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/speech-recognition-and-synthesis/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the advances in speech recognition technology, covering topics such as acoustic modeling using deep neural networks, speaker verification, convolutional neural networks for speech recognition, end-to-end speech recognition systems, hidden Markov models, sequence-to-sequence models, automatic speech recognition, speaker diarization, and statistical language modeling. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t10201 |
| Works | 96 |

## Topic papers all

Showing 15 of 96.

- [Perception of the speech code.](https://scholariq.org/papers/perception-of-the-speech-code/)
- [Applying Conditional Random Fields to Japanese Morphological Analysis](https://scholariq.org/papers/applying-conditional-random-fields-to-japanese-morphological-analysis/)
- [StressSense](https://scholariq.org/papers/stresssense/)
- [Transformer Transducer: A Streamable Speech Recognition Model with Transformer Encoders and RNN-T Loss](https://scholariq.org/papers/transformer-transducer-a-streamable-speech-recognition-model-with-transformer/)
- [Acoustic invariance in speech production: Evidence from measurements of the spectral characteristics of stop consonants](https://scholariq.org/papers/acoustic-invariance-in-speech-production-evidence-from-measurements-of-the/)
- [Very deep convolutional neural networks for raw waveforms](https://scholariq.org/papers/very-deep-convolutional-neural-networks-for-raw-waveforms/)
- [Offline bilingual word vectors, orthogonal transformations and the\n inverted softmax](https://scholariq.org/papers/offline-bilingual-word-vectors-orthogonal-transformations-and-the-n-inverted/)
- [Multisource Transfer Learning With Convolutional Neural Networks for Lung Pattern Analysis](https://scholariq.org/papers/multisource-transfer-learning-with-convolutional-neural-networks-for-lung/)
- [The Dynamics of Lexical Competition During Spoken Word Recognition](https://scholariq.org/papers/the-dynamics-of-lexical-competition-during-spoken-word-recognition/)
- [Offline bilingual word vectors, orthogonal transformations and the inverted softmax](https://scholariq.org/papers/offline-bilingual-word-vectors-orthogonal-transformations-and-the-inverted/)
- [Acoustic differences, listener expectations, and the perceptual accommodation of talker variability.](https://scholariq.org/papers/acoustic-differences-listener-expectations-and-the-perceptual-accommodation-of/)
- [Accent-independent adaptation to foreign accented speech](https://scholariq.org/papers/accent-independent-adaptation-to-foreign-accented-speech/)
- [Speech synthesis from ECoG using densely connected 3D convolutional neural networks](https://scholariq.org/papers/speech-synthesis-from-ecog-using-densely-connected-3d-convolutional-neural/)
- [Feature parsing: Feature cue mapping in spoken word recognition](https://scholariq.org/papers/feature-parsing-feature-cue-mapping-in-spoken-word-recognition/)
- [Automated Detection of Parkinson’s Disease Based on Multiple Types of Sustained Phonations Using Linear Discriminant Analysis and Genetically Optimized Neural Network](https://scholariq.org/papers/automated-detection-of-parkinson-s-disease-based-on-multiple-types-of-sustained/)

## Topic primary papers

Showing 15 of 32.

- [Transformer Transducer: A Streamable Speech Recognition Model with Transformer Encoders and RNN-T Loss](https://scholariq.org/papers/transformer-transducer-a-streamable-speech-recognition-model-with-transformer/)
- [Long Short-Term Memory Recurrent Neural Network for Automatic Speech Recognition](https://scholariq.org/papers/long-short-term-memory-recurrent-neural-network-for-automatic-speech-recognition/)
- [Error back propagation for sequence training of Context-Dependent Deep NetworkS for conversational speech transcription](https://scholariq.org/papers/error-back-propagation-for-sequence-training-of-context-dependent-deep-networks/)
- [Automatic Speech Recognition (ASR) Systems for Children: A Systematic Literature Review](https://scholariq.org/papers/automatic-speech-recognition-asr-systems-for-children-a-systematic-literature/)
- [High-Quality Nonparallel Voice Conversion Based on Cycle-Consistent Adversarial Network](https://scholariq.org/papers/high-quality-nonparallel-voice-conversion-based-on-cycle-consistent-adversarial/)
- [Speaker Anonymization Using X-vector and Neural Waveform Models](https://scholariq.org/papers/speaker-anonymization-using-x-vector-and-neural-waveform-models/)
- [Attention Based On-Device Streaming Speech Recognition with Large Speech Corpus](https://scholariq.org/papers/attention-based-on-device-streaming-speech-recognition-with-large-speech-corpus/)
- [An Exploration of Self-Supervised Pretrained Representations for End-to-End Speech Recognition](https://scholariq.org/papers/an-exploration-of-self-supervised-pretrained-representations-for-end-to-end/)
- [Enhancing Pre-Trained ASR System Fine-Tuning for Dysarthric Speech Recognition Using Adversarial Data Augmentation](https://scholariq.org/papers/enhancing-pre-trained-asr-system-fine-tuning-for-dysarthric-speech-recognition/)
- [Exploring deep learning architectures for automatically grading non-native spontaneous speech](https://scholariq.org/papers/exploring-deep-learning-architectures-for-automatically-grading-non-native/)
- [Personalized Adversarial Data Augmentation for Dysarthric and Elderly Speech Recognition](https://scholariq.org/papers/personalized-adversarial-data-augmentation-for-dysarthric-and-elderly-speech/)
- [Automatic Speaker Recognition from Speech Signals Using Self Organizing Feature Map and Hybrid Neural Network](https://scholariq.org/papers/automatic-speaker-recognition-from-speech-signals-using-self-organizing-feature/)
- [A Comparative Study on Non-Autoregressive Modelings for Speech-to-Text Generation](https://scholariq.org/papers/a-comparative-study-on-non-autoregressive-modelings-for-speech-to-text/)
- [End-to-End Training of a Large Vocabulary End-to-End Speech Recognition System](https://scholariq.org/papers/end-to-end-training-of-a-large-vocabulary-end-to-end-speech-recognition-system-2/)
- [Self-Supervised ASR Models and Features for Dysarthric and Elderly Speech Recognition](https://scholariq.org/papers/self-supervised-asr-models-and-features-for-dysarthric-and-elderly-speech/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.