Initializing new dataset: All Bambara ASR

.gitattributes

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+*.wav filter=lfs diff=lfs merge=lfs -text
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
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+*.npy filter=lfs diff=lfs merge=lfs -text
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+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
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+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+# Video files - compressed
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.webm filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language: 
+- bm  # ISO 639-1 code for Bambara
+- fr  # ISO 639-1 code for French
+pretty_name: "Bambara-ASR-All Audio Dataset"
+version: "1.0.0"  # Explicit versioning
+tags:
+- audio
+- transcription
+- multilingual
+- Bambara
+- French
+license: "cc-by-4.0" 
+task_categories:
+- automatic-speech-recognition
+- text-to-speech
+- translation
+task_ids:
+- audio-language-identification  # Identifying languages in audio
+- keyword-spotting              # Detecting keywords in audio
+annotations_creators:
+- semi-expert
+language_creators:
+- crowdsourced  # If the data was annotated or recorded by a team
+source_datasets:
+- jeli-asr  
+- mali-pense
+- reading-tutor-data-collection
+size_categories:
+- 10GB<
+- 10K<n<100K
+dataset_info:
+  audio_format: "wav"
+  features:
+  - name: audio
+    dtype: audio
+  - name: duration
+    dtype: float
+  - name: bam
+    dtype: string
+  - name: french
+    dtype: string
+  total_audio_files: 38769 
+  total_duration_hours: ~37
+
+configs:
+- config_name: jeli-asr-rmai
+  data_files:
+  - split: train
+    path: "jeli-asr-rmai/train/*"
+  - split: test
+    path: "jeli-asr-rmai/test/*"
+- config_name: bam-asr-oza
+  data_files:
+  - split: train
+    path: "bam-asr-oza/train/*"
+  - split: test
+    path: "bam-asr-oza/test/*"
+  config_name: oza-mali-pense
+  data_files:
+  - split: train
+    path: "oza-mali-pense/train/*"
+  config_name: rt-data-collection
+  data_files:
+  - split: train
+    path: "rt-data-collection/*"
+- config_name: jeli-asr
+  data_files:
+  - split: train
+    path: 
+      - "jeli-asr-rmai/train/*"
+      - "bam-asr-oza/train/*"
+  - split: test
+    path: 
+      - "jeli-asr-rmai/test/*"
+      - "bam-asr-oza/test/*"
+  config_name: bam-asr-all
+  default: true
+  data_files:
+  - split: train
+    path: 
+      - "jeli-asr-rmai/train/*"
+      - "bam-asr-oza/train/*"
+      - "oza-mali-pense/train/*"
+      - "rt-data-collection/*"
+  - split: test
+    path: 
+      - "jeli-asr-rmai/test/*"
+      - "bam-asr-oza/test/*"
+description: |
+  This Dataset is a multilingual audio dataset containing audio samples in Bambara with semi-expert transcriptions and French translations. 
+  Each audio file is paired with its transcription in Bambara or its translation in French (available in manifest files). 
+  The dataset is designed for tasks like automatic speech recognition (ASR) and translation. Data come from all publicly available sources providing audios and aligned bambara transcription.
+---
+
+# All Bambara ASR Dataset
+
+This dataset aims to gather all publicly available Bambara ASR datasets. It is primarily composed of the **Jeli-ASR** dataset (available at [RobotsMali/jeli-asr](https://huggingface.co/datasets/RobotsMali/jeli-asr)), along with the **Mali-Pense** data curated and published by Aboubacar Ouattara (available at [oza75/bambara-tts](https://huggingface.co/datasets/oza75/bambara-tts)). Additionally, it includes 1 hour of audio recently collected by the RobotsMali AI4D Lab, featuring children's voices reading some of RobotsMali GAIFE books. This dataset is desihgned for automatic speech recognition (ASR) task primarily.
+
+## Important Note
+
+Please note that this dataset is currently in development and is therefore not fixed. The structure, content, and availability of the dataset may change as improvements and updates are made.
+
+---
+
+## **Directory Structure**
+
+```
+bam-asr-all/
+|
+├── README.md
+├── metadata.jsonl
+├── manifests/
+│   ├── jeli-asr-rmai-test-manifest.json
+│   ├── jeli-asr-rmai-train-manifest.json
+│   ├── oza-bam-asr-test-manifest.json
+│   └── oza-bam-asr-train-manifest.json
+│   └── oza-mali-pense-train-manifest.json
+│   └── reading-tutor-train-manifest.jon
+│   └── train-manifest.json # jeli-asr-rmai-train-manifest.json + oza-bam-asr-train-manifest.json
+│   └── test-manifest.json # jeli-asr-rmai-test-manifest.json + oza-bam-asr-test-manifest.json
+│
+├── french-manifests/
+│   ├── jeli-asr-rmai-test-french-manifest.json
+│   ├── jeli-asr-rmai-train-french-manifest.json
+│   ├── oza-bam-asr-test-french-manifest.json
+│   └── oza-bam-asr-train-french-manifest.json
+│   └── oza-mali-pense-train-french-manifest.json
+│
+├── jeli-asr-rmai/
+│   ├── train/
+│   └── test/
+│
+├── bam-asr-oza/
+│   ├── train/
+│   └── test/
+|
+├── oza-mali-pense/
+│   ├── train/
+|
+├── oza-mali-pense/
+```
+
+### **manifests Directory**
+This directory contains the manifest files used for training speech recognition (ASR) and text-to-speech (TTS) models. Those are JSON files:
+
+Each line in the manifest files is a JSON object with the following structure:
+```json
+{
+  "audio_filepath": "bam-asr-all/rt-data-collection/zctn7pFmtmR45FKym7d5.wav", 
+  "duration": 10.24, 
+  "text": "Ni Birituban dɔ tun bɛ se ka piyano fɔ, a tun bɛ fara Sɛ kan dɔnkilida la."
+}
+```
+- **audio_filepath**: The relative path to the corresponding audio file.
+- **duration**: The duration of the audio file in seconds.
+- **text**: The transcription of the audio in Bambara.
+
+### 3. **french-manifests/**
+This directory contains French equivalent manifest files for the dataset. The structure is similar to the `manifests/` directory but with French transcriptions
+
+---
+
+## **Dataset Details**
+
+- **Total Duration**: 37.41 hours
+- **Number of Samples**: 38,769 
+  - **Training Set**: 37,306 samples
+  - **Testing Set**: 1,463 samples
+
+### **Subsets**:
+
+- **Oza's Bambara-ASR**: \~29 hours (clean subset).
+- **Jeli-ASR-RMAI**: \~3.5 hours (filtered subset).
+- **oza-tts-mali-pense**: \~4 hours
+- **reading-tutor-data-collection**: \~1 hour
+
+---
+
+## **Usage**
+
+The manifest files are specifically created for training Automatic Speech Recognition (ASR) models in NVIDIA NeMo framework, but they can be used with any other framework that supports manifest-based input formats or reformatted for other use cases.
+
+To use the dataset, simply load the manifest files (`train-manifest.json` and `test-manifest.json`) in your training script. The file paths for the audio files and the corresponding transcriptions are already provided in these manifest files You can also load it directly in a HuggingFace dataset object.
+
+### Downloading the Dataset:
+
+```python
+from datasets import load_dataset
+
+# Clone dataset repository maintaining directory structure
+!git clone https://huggingface.co/datasets/RobotsMali/jeli-asr
+
+#  Or
+
+# Load the dataset into Hugging Face Dataset object
+dataset = load_dataset("RobotsMali/bam-asr-all")
+```
+
+## **Known Issues**
+
+While significantly improved, this dataset may still contain a few Slightly misaligned samples. It has conserved most of the issues of the original dataset such as: 
+
+- Inconsistent  transcriptions
+- Non-standardized naming conventions.
+- Language and spelling issues
+
+---
+
+## **Citation**
+
+If you use this dataset in your research or project, please credit the creators of the original datasets.
+
+- **Jeli-ASR dataset**: [Original Jeli-ASR Dataset](https://github.com/robotsmali-ai/jeli-asr). 
+- **Oza's Bambara-ASR dataset**: [oza75/bambara-asr](https://huggingface.co/datasets/oza75/bambara-asr)

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