https://github.com/Alizeded/BERP
공식 코드BERP: A Blind Estimator of Room Parameters for Single-Channel Noisy Speech Signals
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Room Impulse Response (RIR) is an audio signal processing task that involves capturing and analyzing the acoustic characteristics of a room or an environment. The goal is to measure and model the way sound waves interact with the space, including reflections, reverberation, and echoes.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
BERP: A Blind Estimator of Room Parameters for Single-Channel Noisy Speech Signals
dEchorate: a Calibrated Room Impulse Response Database for Echo-aware Signal Processing
gpuRIR: A python library for Room Impulse Response simulation with GPU acceleration
StoRIR: Stochastic Room Impulse Response Generation for Audio Data Augmentation
FAST-RIR: Fast neural diffuse room impulse response generator
ArrayDPS: Unsupervised Blind Speech Separation with a Diffusion Prior
FRA-RIR: Fast Random Approximation of the Image-source Method
Attack on practical speaker verification system using universal adversarial perturbations
gpuRIR: A python library for Room Impulse Response simulation with GPU acceleration
FAST-RIR: Fast neural diffuse room impulse response generator
FAST-RIR: Fast neural diffuse room impulse response generator
gpuRIR: A python library for Room Impulse Response simulation with GPU acceleration
Filtered Noise Shaping for Time Domain Room Impulse Response Estimation From Reverberant Speech
dEchorate: a Calibrated Room Impulse Response Database for Echo-aware Signal Processing
FRA-RIR: Fast Random Approximation of the Image-source Method
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.