speaker verification

Beike Product & Technology

Dec 23, 2021 · Artificial Intelligence

KeSpeech: A Large-Scale Chinese Mandarin Dialect Speech Benchmark Presented at NeurIPS 2021

KeSpeech, a benchmark jointly released by Beike AI and Tsinghua University at NeurIPS 2021, provides a massive Chinese Mandarin dialect dataset covering 30,000 speakers from 34 cities, supporting speech recognition, speaker verification, dialect identification, and voice conversion tasks, and includes rich multi‑scenario and parallel corpora for advanced research.

AINeurIPSSpeech Recognition

0 likes · 5 min read

KeSpeech: A Large-Scale Chinese Mandarin Dialect Speech Benchmark Presented at NeurIPS 2021

58 Tech

Jun 3, 2020 · Artificial Intelligence

Speaker Verification System for Detecting Spam Calls in 58 Used‑Car Platform

This article describes how the 58 used‑car team built a speaker‑verification pipeline—covering data collection, MFCC feature extraction, LSTM and GMM modeling, threshold tuning, multi‑speaker clustering, and deployment results—to automatically block nuisance telemarketing calls while preserving user privacy.

GMMLSTMMFCC

0 likes · 15 min read

Speaker Verification System for Detecting Spam Calls in 58 Used‑Car Platform

HomeTech

Feb 19, 2020 · Artificial Intelligence

Voiceprint-Based Gender Recognition Using GMM‑UBM and i‑Vector Modeling for 400‑Call Center Audio

This article presents a complete voiceprint gender identification pipeline for 400‑call center recordings, detailing acoustic feature extraction, GMM‑UBM training, Joint Factor Analysis, i‑vector extraction, and logistic regression classification, achieving a reported accuracy of 97.8%.

GMM-UBMacoustic featuresgender recognition

0 likes · 11 min read

Voiceprint-Based Gender Recognition Using GMM‑UBM and i‑Vector Modeling for 400‑Call Center Audio

Alibaba Cloud Infrastructure

Dec 17, 2016 · Artificial Intelligence

Understanding Voiceprint Recognition: Principles, Techniques, and Applications

The article explains voiceprint (speaker) recognition technology, covering its biological basis, 1:1 verification versus 1:N identification, content‑related versus content‑independent approaches, key acoustic features such as MFCC, the iVector framework, system workflow diagrams, and its use in an Alibaba security challenge.

artificial intelligencebiometricsmachine learning

0 likes · 10 min read

Understanding Voiceprint Recognition: Principles, Techniques, and Applications