Update README.md

README.md

@@ -46,4 +46,94 @@ library_name: pyannote-audio
 tags:
 - music
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-#
+# SoundSlayerAI
+
+SoundSlayerAI is an innovative project that focuses on music-related tasks and utilizes the power of the "pyannote-audio" library. This project aims to provide various functionalities for audio analysis and processing, making it easier to work with music datasets.
+
+## Datasets
+
+SoundSlayerAI makes use of the following datasets:
+
+- Fhrozen/AudioSet2K22
+- Chr0my/Epidemic_sounds
+- ChristophSchuhmann/lyrics-index
+- Cropinky/rap_lyrics_english
+- tsterbak/eurovision-lyrics-1956-2023
+- brunokreiner/genius-lyrics
+- google/MusicCaps
+- ccmusic-database/music_genre
+- Hyeon2/riffusion-musiccaps-dataset
+- SamAct/autotrain-data-musicprompt
+- Chr0my/Epidemic_music
+- juliensimon/autonlp-data-song-lyrics
+- Datatang/North_American_English_Speech_Data_by_Mobile_Phone_and_PC
+- Chr0my/freesound.org
+- teticio/audio-diffusion-256
+- KELONMYOSA/dusha_emotion_audio
+- Ar4ikov/iemocap_audio_text_splitted
+- flexthink/ljspeech
+- mozilla-foundation/common_voice_13_0
+- facebook/voxpopuli
+- SocialGrep/one-million-reddit-jokes
+- breadlicker45/human-midi-rlhf
+- breadlicker45/midi-gpt-music-small
+- projectlosangeles/Los-Angeles-MIDI-Dataset
+- huggingartists/epic-rap-battles-of-history
+- SocialGrep/one-million-reddit-confessions
+- shahules786/prosocial-nsfw-reddit
+- Thewillonline/reddit-sarcasm
+- autoevaluate/autoeval-eval-futin__guess-vi-4200fb-2012366606
+- lmsys/chatbot_arena_conversations
+- mozilla-foundation/common_voice_11_0
+- mozilla-foundation/common_voice_4_0
+
+## Library
+
+The core library used in this project is "pyannote-audio." This library provides a wide range of functionalities for audio analysis and processing, making it an excellent choice for working with music datasets. The "pyannote-audio" library offers a comprehensive set of tools and algorithms for tasks such as audio segmentation, speaker diarization, music transcription, and more.
+
+## Metrics
+
+To evaluate the performance of SoundSlayerAI, several metrics are employed, including:
+
+- Accuracy
+- Bertscore
+- BLEU
+- BLEURT
+- Brier Score
+- Character
+
+These metrics help assess the effectiveness and accuracy of the implemented algorithms and models.
+
+## Language
+
+The SoundSlayerAI project primarily focuses on the English language. The datasets and models used in this project are optimized for English audio and text analysis tasks.
+
+## Usage
+
+To use SoundSlayerAI, follow these steps:
+
+1. Install the required dependencies by running `pip install pyannote-audio`.
+
+2. Import the necessary modules from the "pyannote.audio" package to access the desired functionalities.
+
+3. Load the audio data or use the provided datasets to perform tasks such as audio segmentation, speaker diarization, music transcription, and more.
+
+4. Apply the appropriate algorithms and models from the "pyannote.audio" library to process and analyze the audio data.
+
+5. Evaluate the results using the specified metrics, such as accuracy, bertscore, BLEU, BLEURT, brier_score, and character.
+
+6. Iterate and refine your approach to achieve the desired outcomes for your music-related tasks.
+
+## License
+
+SoundSlayerAI is released under the Openrail license. Please refer to the LICENSE file for more details.
+
+## Contributions
+
+Contributions to SoundSlayerAI are welcome! If you have any ideas, bug fixes, or enhancements, feel free to submit a pull request or open an issue on the GitHub repository.
+
+## Contact
+
+For any inquiries or questions regarding SoundSlayerAI, please reach out to the project maintainer at [insert email address].
+
+Thank you for your interest in SoundSlayerAI!