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✰𝑨𝑰 𝑺𝑪𝑯𝑬𝑴𝑨 𝑭𝑶𝑹 𝑬𝑼𝑺𝑶𝑵𝑼𝑺✰
🪷 Level 1 🪷
Sound 🎤 Recognition
⭐Objective⭐
⭐ Develop an AI algorithm that can accurately capture and
recognize live audio input from the VR headset or device.
🦋Tasks🦋
🐛 Integrate microphone access.
🐛 Implement a frequency detection algorithm similar to tuners.
🐛 Test the accuracy of sound recognition in various environments.
Level 1: Sound Recognition
1.1 Microphone Integration
Task: Ensure the VR headset or device can access and capture live audio.
Roadmap:
Research and select the best microphone access library or API compatible with the VR device.
Implement microphone access in the experience.
Test microphone access across different VR devices to ensure compatibility.
1.2 Frequency Detection
Task: Implement an algorithm to detect the frequency of the captured sound.
Roadmap:
Research existing frequency detection algorithms. Some potential references from GitHub include:
DeepSpeech: An open-source speech-to-text engine.
Whisper: OpenAI's model for speech recognition.
Leon: An open-source personal assistant with sound recognition capabilities.
Integrate the chosen algorithm into the experience.
Test the algorithm's accuracy with various sound inputs.
1.3 Sound Classification
Task: Classify the detected sound into predefined categories or moods.
Roadmap:
Define the categories or moods you want to classify the sounds into.
Train a machine learning model using labeled sound data or use a pre-trained model.
Integrate the classification model into the experience.
Test the model's accuracy and refine as necessary.
1.4 Real-time Processing
Task: Ensure the sound recognition and processing happen in real-time without noticeable lag.
Roadmap:
Optimize the algorithms for speed and efficiency.
Test the experience in real-world scenarios to ensure real-time processing.
Make necessary adjustments based on feedback and testing results.
1.5 Feedback Loop
Task: Implement a feedback mechanism for users to correct any misclassifications or provide input on the recognized sound.
Roadmap:
Design a user-friendly interface for feedback within the experience.
Use the feedback to continuously improve the sound recognition algorithm.
Periodically retrain the model with new data and feedback.