Member Avatar for lich

hi,

have anyone done a research or any project in noise reduction. im doing a project in speech recognition. i want to use noise reduction as well. but dont know how the process works. if someone can help me out for that

  • 2 Contributors
  • 5 Replies
  • 111 Views
  • 1 Day Discussion Span
  • Latest Post Latest Post by Salem

Dani AI

Generated

For (and following ’s prompt): here is a compact, practical starter you can use for a speech‑recognition final year project. It focuses on approaches that actually help ASR, gives a minimal Python example, and points to reliable tools.

Noise‑reduction approaches and tradeoffs

  • Two families: classical signal processing (spectral subtraction, Wiener filtering, spectral gating) and data‑driven models (DNN denoisers, RNNs like RNNoise).
  • Important: a front‑end that “sounds better” can still harm ASR because it changes spectral cues. Always evaluate by word error rate (WER) on your recognizer, not only by listening or by perceptual scores. In many cases multi‑condition training / data augmentation (adding noise to training data) yields larger WER gains than aggressive enhancement.

Quick reproducible pipeline (Python)

  1. record or load audio, 2) pick a short noise-only segment, 3) apply a denoiser, 4) extract features (MFCC/FBANK), 5) evaluate ASR.
    Example using common Python tools:
import librosa
import noisereduce as nr

y, sr = librosa.load('speech.wav', sr=None)
noise_clip = y[:int(0.5*sr)]   # first 0.5s assumed noise
clean = nr.reduce_noise(y=y, sr=sr, y_noise=noise_clip)

Useful libraries and demos

Troubleshooting tips

  • If WER increases after enhancement: reduce processing strength, use less aggressive gain, or switch to multi‑condition training.
  • Watch for musical noise (spectral subtraction artifacts); smaller frame shifts and smoother noise estimates help.
  • If you have multiple microphones, beamforming (delay‑and‑sum, MVDR) often beats single‑channel denoising.

For academic reading, look up classic papers by Boll (spectral subtraction) and Ephraim & Malah (MMSE-STSA) via your university library to understand theory.

Recommended Answers

All 5 Replies

Member Avatar for lich

ya i did some. but needed some more support. its bit hard to understand like that. my final year project is about speech recognition. so i need to do some mechanisms in noise reduction also. but dont know how it process

Member Avatar for lich

any supporting pdf

commented: fail -1
Be a part of the DaniWeb community

We're a friendly, industry-focused community of developers, IT pros, digital marketers, and technology enthusiasts meeting, networking, learning, and sharing knowledge.