Real-Time Speech Recognition: A Developer's Guide

1import librosa
2import numpy as np
3
4# Load an audio file
5y, sr = librosa.load('audio.wav')
6
7# Extract MFCC features (Mel-Frequency Cepstral Coefficients)
8mfccs = librosa.feature.mfcc(y=y, sr=sr, n_mfcc=40)
9
10# Print the shape of the MFCCs
11print(mfccs.shape)
12
13# Can also compute other features like spectral centroid, bandwidth, etc.
14

1import nltk
2from nltk.util import ngrams
3
4# Sample text
5text = "The quick brown fox jumps over the lazy dog"
6
7# Tokenize the text
8tokens = nltk.word_tokenize(text)
9
10# Create n-grams (e.g., bigrams)
11n = 2
12bigrams = ngrams(tokens, n)
13
14# Print the bigrams
15for gram in bigrams:
16    print(gram)
17
18# In a real system, you'd calculate probabilities based on a large corpus
19

1import speech_recognition as sr
2
3# Initialize recognizer
4r = sr.Recognizer()
5
6# Set up microphone
7microphone = sr.Microphone()
8
9with microphone as source:
10    print("Say something!")
11    r.adjust_for_ambient_noise(source)  # Reduce noise
12    audio = r.listen(source)
13
14
15try:
16    # Use Google Speech Recognition
17    text = r.recognize_google(audio)
18    print("Google Speech Recognition thinks you said: " + text)
19except sr.UnknownValueError:
20    print("Google Speech Recognition could not understand audio")
21except sr.RequestError as e:
22    print("Could not request results from Google Speech Recognition service; {0}".format(e))
23
24# This is a simple example. For real-time, you'd use a streaming API.
25

1// This is a simplified example and requires a suitable speech recognition library
2// or API integration (e.g., using the Web Speech API).
3
4function startRecognition() {
5  // Check for browser support
6  if ('webkitSpeechRecognition' in window) {
7    const recognition = new webkitSpeechRecognition();
8
9    recognition.continuous = true;
10    recognition.interimResults = true;
11
12    recognition.onstart = function() {
13      console.log("Speech recognition started");
14    };
15
16    recognition.onresult = function(event) {
17      let interim_transcript = '';
18      let final_transcript = '';
19
20      for (let i = event.resultIndex; i < event.results.length; ++i) {
21        if (event.results[i].isFinal) {
22          final_transcript += event.results[i][0].transcript;
23        } else {
24          interim_transcript += event.results[i][0].transcript;
25        }
26      }
27
28      // Update the UI with the transcript
29      document.getElementById('final').innerHTML = final_transcript;
30      document.getElementById('interim').innerHTML = interim_transcript;
31    };
32
33    recognition.onerror = function(event) {
34      console.error("Speech recognition error:", event.error);
35    };
36
37    recognition.onend = function() {
38      console.log("Speech recognition ended");
39    };
40
41    recognition.start();
42  } else {
43    console.log("Speech Recognition not supported");
44  }
45}
46
47// Call startRecognition() to begin the process
48