Wei Chu Email & Phone Number

• Customized Large-Scale Datasets ** Olewave delivers customized, labeled, and validated large-scale real-world NLP/CV/speech/multimodal datasets of various scenarios such as dictation and conversation in multi.
• topic-specific text datasets for training your own LLM model
• visual/video/image datasets with tags/prompts for training your own CV model
• speech/audio datasets of different languages and dialects for training your own ASR/Whisper/SeamlessM4T/TTS model.
• and multimodal datasets.We constantly collect timely data from languages including Latin America Spanish, Arabic, Southeast Asian, Chinese, Japanese, Korean.1/3-1/10 in data pricing vs. traditional data vendors with.
• AI-powered Accuracy: Transcribe any audio, regardless of language, dialect, accent, or topic, with exceptional accuracy. We surpass the competition in understanding even the most challenging recordings.

Shenzhen, Guangdong, CN

To PhD students who are interested in doing research on but not limited to Seq2Seq-based large vocabulary continuous speech recognition (RNN-T) and spoken language understanding (End-to-End-based Conversational AI) with me, feel free to send your CV/resume to wei.w.chu@gmail.com.I have supervised 10+ interns, most of them ended their internship with.

Shanghai, Shanghai, CN

1) Full-stack development and improvement of acoustic, pronunciation, language modeling, and decoder optimization for streaming non-native large vocabulary continuous speech recognitiona. Acoustic Modeling (Research & Development): i. Multi-Task Learning on a limited amount of training data collected from each task. ii. Using Adversarial training to train.

Santa Monica, California, US

As the first Speech Research Scientist and Engineer at Snap Research, promptly prototype, build and customize speech recognition services, keyword spotting in audio services, and audio/speech processing libraries for product teams.1. Robust Closed Captioning for Audio Content-- Worked with News/Ads/User Content teams to customize the above speech.

San Mateo, California, US

-- Built and delivered production-level Deep Neural Network (DNN)-based models for speech recognition.-- Built a low-cost but yet high-performance CPU+GPU computing cluster for deep learning experiments.-- Designed and implemented new practical algorithms for improving the performance of speech recognition.-- Handled practical aspects of a production-level.

Santa Clara, California, US

Learning the skills of handling issues from vendors, customers, and internal develop and debug teams. Designed and built a test system for internal teams, customers and vendors. Learned how a corporation operates.

San Diego, California, US

Understood the key aspects in a successful Interactive Voice Response (IVR) system. Also learned how a middle-sized company operates.

Earned 500k funding for the company. Also learned how a startup operates.

Redmond, Washington, US

Audio-visual-depth automatic speech recognition on Kinect.

Los Angeles, CA, US

Worked out very accurate noise robust pitch estimation and tracking algorithm.Pioneer study in bird song classification, recognition, and detection.

Los Angeles, CA, US

Micrphone array-based kid speech recognition..

Arlington, Virginia, US

Statistically-based Letter-To-Sound conversion.

Cambridge, MA, US

Discriminative training for speech recognition.

Redmond, Washington, US

Acoustic event detection.

Santa Clara, California, US

Speaker segmentation and clustering.

Ph.D., Electrical Engineering

M.S., Electrical Engineering

B.E., Electronic Engineering

Doctor Of Philosophy - Phd, Signal And Systems