A5061980970- Speech and Audio Processing
- Speech Recognition and Synthesis
- Music and Audio Processing
- Hematological disorders and diagnostics
- Liver Disease Diagnosis and Treatment
- Thermal Regulation in Medicine
- Tuberculosis Research and Epidemiology
- COVID-19 diagnosis using AI
- Infectious Diseases and Tuberculosis
- Probiotics and Fermented Foods
- Pharmacological Effects of Natural Compounds
- Clostridium difficile and Clostridium perfringens research
- Gut microbiota and health
- Metabolism and Genetic Disorders
- Hepatitis B Virus Studies
- Retinoids in leukemia and cellular processes
- Hemoglobinopathies and Related Disorders
- Toxin Mechanisms and Immunotoxins
- Diet, Metabolism, and Disease
- Natural Products and Biological Research
- Neonatal Health and Biochemistry
- Renal function and acid-base balance
- Liver Disease and Transplantation
- Pneumonia and Respiratory Infections
- Hepatitis C virus research
Google (United States)
2009-2022
Vancouver Biotech (Canada)
2022
We present a novel recurrent neural network (RNN) model for voice activity detection. Our multi-layer RNN model, in which nodes compute quadratic polynomials, outperforms much larger baseline system composed of Gaussian mixture models (GMMs) and hand-tuned state machine (SM) temporal smoothing. All parameters our are optimized together, so that it properly weights its preference continuity against the acoustic features each frame. uses one tenth GMM+SM by 26% reduction false alarms, reducing...
Robust and far-field speech recognition is critical to enable true hands-free communication. In conditions, signals are attenuated due distance. To improve robustness loudness variation, we introduce a novel frontend called per-channel energy normalization (PCEN). The key ingredient of PCEN the use an automatic gain control based dynamic compression replace widely used static (such as log or root) compression. We evaluate on keyword spotting task. On our large rerecorded noisy eval sets,...
Background The World Health Organization (WHO) recommends chest radiography to facilitate tuberculosis (TB) screening. However, radiograph interpretation expertise remains limited in many regions. Purpose To develop a deep learning system (DLS) detect active pulmonary TB on radiographs and compare its performance that of radiologists. Materials Methods A DLS was trained tested using retrospective (acquired between 1996 2020) from 10 countries. improve generalization, large-scale pretraining,...
ABSTRACT Changes to gut environmental factors such as pH and osmolality due disease or drugs correlate with major shifts in microbiome composition; however, we currently cannot predict which species can tolerate changes how the community will be affected. Here, assessed growth of 92 representative human bacterial strains spanning 28 families across multiple values osmolalities vitro . The ability grow extreme conditions correlated availability known stress response genes many cases, but not...
We present a system for quickly and cheaply building transcribed speech corpora containing utterances from many speakers in variety of acoustic conditions. The consists client application running on an Android mobile device with intermittent Internet connection to server. collects demographic information about the speaker, fetches textual prompts server speaker read, records speaker’s voice, uploads audio associated metadata has so far been used collect over 3000 hours 17 languages around...
Letter units, or graphemes, have been reported in the literature as a surprisingly effective substitute to more traditional phoneme at least languages that enjoy strong correspondence between pronunciation and orthography. For English however, where letter symbols less acoustic consistency, previously results fell short of systems using highly-tuned lexicons. Grapheme units simplify system design, but since graphemes map wider set realizations than phonemes, we should expect grapheme-based...
This paper presents a robust, small-footprint, far-field keyword spotting (KWS) algorithm, which was inspired by the human auditory system's ability to achieve so-called cocktail party effect in adverse acoustic environments. It introduces idea of combining microphone-array speech enhancement with machine learning, incorporating feedback path from neural network (NN) KWS classifier its signal preprocessing frontend so that noise reduction can benefit from, and turn, better serve backend...
We consider the task of speech recognition with loud music background interference. use model-based music-speech separation and train GMM models for on audio prior to speech. show over 8% relative improvement in WER at 10 dB SNR a real world Voice Search ASR system. investigate relationship between accuracy amount used as prologue size models. Our study shows that performance peaks when using around 6 seconds model. hypothesize this is due dynamic nature structure popular music. Adding more...
_MEDICALJOURNAS magniesium sulphate and digitalis.Tinned meat, fresh salmon, codfislh, albumini water, butter, aiid white bread formed the basis of tlle diet, anid wlholemeal bread, wheat germ, cabbages, beanis, or peas were Inot given.These foodstuffs fed in small amounts at frequent intervals as palatable a form possible.The patient remainied onl this diet for four days, during which time she gor rapidly worse.The ascites increased, her con- dition became critical.Paracentesis abdominis...
Abstract Changes to gut environmental factors such as pH and osmolality due disease or drugs correlate with major shifts in microbiome composition; however, we currently cannot predict which species can tolerate changes how the community will be affected. Here, assessed growth of 92 representative human bacterial strains spanning 28 families across multiple values osmolalities vitro . The ability grow extreme conditions correlated availability known stress response genes many cases, but not...
Robust and far-field speech recognition is critical to enable true hands-free communication. In conditions, signals are attenuated due distance. To improve robustness loudness variation, we introduce a novel frontend called per-channel energy normalization (PCEN). The key ingredient of PCEN the use an automatic gain control based dynamic compression replace widely used static (such as log or root) compression. We evaluate on keyword spotting task. On our large rerecorded noisy eval sets,...
Tuberculosis (TB) is a top-10 cause of death worldwide. Though the WHO recommends chest radiographs (CXRs) for TB screening, limited availability CXR interpretation barrier. We trained deep learning system (DLS) to detect active pulmonary using CXRs from 9 countries across Africa, Asia, and Europe, utilized large-scale pretraining, attention pooling, noisy student semi-supervised learning. Evaluation was on (1) combined test set spanning China, India, US, Zambia, (2) an independent mining...