Audio Enhancement in SipPulse AI

Overview

SipPulse AI offers advanced audio processing technologies to enhance sound quality, remove unwanted noise, and separate different audio components. These tools are essential for professional communications, content production, and audio analysis.

Audio Enhancement

Audio enhancement uses advanced algorithms to improve clarity, intelligibility, and overall quality of audio recordings.

Key Features:

• Clarity Enhancement: Improves the sharpness of voices and other main sounds
• Volume Normalization: Adjusts audio levels for optimal consistency
• Equalization Correction: Optimizes frequency balance for higher quality
• Reverberation Reduction: Minimizes echoes and environmental effects

Usage Example:

import requests

def enhance_audio(audio_file_path, api_key):
    """
    Enhances an audio file using the SipPulse AI API
    
    Parameters:
    - audio_file_path (str): Path to the audio file
    - api_key (str): Your SipPulse API key
    
    Returns:
    - dict: API response containing information about the enhanced audio
    """
    url = "https://api.sippulse.ai/audio-enhancement"
    
    headers = {
        "accept": "application/json",
        "api-key": api_key
    }
    
    with open(audio_file_path, "rb") as file:
        files = {"file": (audio_file_path, file, "audio/mpeg")}
        response = requests.post(url, headers=headers, files=files)
    
    if response.status_code == 200:
        return response.json()
    else:
        raise Exception(f"Error {response.status_code}: {response.text}")

# Example usage
result = enhance_audio("meeting_recording.mp3", "YOUR_API_KEY")
print(f"Enhanced audio saved at: {result['enhanced_audio_url']}")

Noise Reduction

Noise reduction identifies and removes unwanted sounds, such as background noise, hums, static, and other disturbances that compromise audio quality.

Types of Noise Treated:

• Environmental Noise: Fans, air conditioning, traffic
• Electrical Noise: Hums, equipment buzzing
• Microphone Noise: Handling noises, wind
• Transmission Noise: Digital artifacts, network failures

Usage Example:

const axios = require('axios');
const fs = require('fs');
const FormData = require('form-data');

/**
 * Reduces noise in an audio file using the SipPulse AI API
 * 
 * @param {string} audioFilePath - Path to the audio file
 * @param {string} apiKey - Your SipPulse API key
 * @param {number} intensity - Noise reduction intensity (1-10)
 * @returns {Promise} - Promise resolving to the API response
 */
async function reduceNoise(audioFilePath, apiKey, intensity = 5) {
  const url = 'https://api.sippulse.ai/noise-reduction';
  
  const formData = new FormData();
  formData.append('file', fs.createReadStream(audioFilePath));
  formData.append('intensity', intensity);
  
  const headers = {
    'accept': 'application/json',
    'api-key': apiKey,
    ...formData.getHeaders()
  };
  
  try {
    const response = await axios.post(url, formData, { headers });
    return response.data;
  } catch (error) {
    throw new Error(`Error: ${error.response ? error.response.data : error.message}`);
  }
}

// Example usage
(async () => {
  try {
    const result = await reduceNoise('noisy_interview.mp3', 'YOUR_API_KEY', 7);
    console.log(`Audio with reduced noise: ${result.processed_audio_url}`);
  } catch (error) {
    console.error(error.message);
  }
})();

Audio Separation

Audio separation divides a recording into its individual components, such as voices, background music, and sound effects. This technology uses advanced neural networks to identify and isolate different sound sources.

Separation Capabilities:

• Voice/Music Separation: Isolates voices from background music
• Multiple Speaker Separation: Separates different people speaking
• Instrument Isolation: Extracts specific instruments from a mix
• Element Removal: Eliminates unwanted components from audio

Usage Example:

import requests
import json

def separate_audio(audio_file_path, api_key, separation_type="voice_music"):
    """
    Separates audio components using the SipPulse AI API
    
    Parameters:
    - audio_file_path (str): Path to the audio file
    - api_key (str): Your SipPulse API key
    - separation_type (str): Type of separation to apply
                            ("voice_music", "multi_speaker", "instruments")
    
    Returns:
    - dict: API response containing URLs for the separated components
    """
    url = "https://api.sippulse.ai/audio-separation"
    
    headers = {
        "accept": "application/json",
        "api-key": api_key
    }
    
    with open(audio_file_path, "rb") as file:
        files = {
            "file": (audio_file_path, file, "audio/mpeg"),
            "settings": (None, json.dumps({"separation_type": separation_type}), "application/json")
        }
        response = requests.post(url, headers=headers, files=files)
    
    if response.status_code == 200:
        return response.json()
    else:
        raise Exception(f"Error {response.status_code}: {response.text}")

# Example usage
result = separate_audio("podcast_with_music.mp3", "YOUR_API_KEY", "voice_music")
print(f"Voice component: {result['voice_track_url']}")
print(f"Music component: {result['music_track_url']}")

Practical Applications

• Contact Centers: Improves call quality for analysis and training
• Virtual Meetings: Reduces background noise for clearer communications
• Content Production: Separates audio elements for professional editing
• Telemedicine: Enhances voice quality for more accurate diagnoses
• Transcription: Prepares audio for STT processing with greater accuracy
• Surveillance: Isolates and amplifies specific sounds for security analysis

Integrating with the API

To use these features via API, you can use the following curl command:

curl -X 'POST' \
  'https://api.sippulse.ai/audio-enhancement' \
  -H 'accept: application/json' \
  -H 'api-key: $SIPPULSE_API_KEY' \
  -F 'file=your_audio_file.mp3;type=audio/mpeg'

Our API supports the following audio formats: MP3, WAV, M4A, AAC, FLAC, and OGG, with a maximum file size of 25MB.