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README.md

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+---
+language:
+- ha
+license: cc-by-4.0
+pretty_name: Hausa Long Voice Dataset
+size_categories:
+- 100<n<1K
+task_categories:
+- text-to-speech
+- automatic-speech-recognition
+task_ids:
+- text-to-speech
+- speaker-identification
+---
+
+# Dataset Card for "hausa_long_voice_dataset"
+
+## Dataset Overview
+
+**Dataset Name**: Hausa Long Voice Dataset
+
+**Description**: This dataset contains merged Hausa language audio samples from Common Voice. Audio files from the same speaker have been concatenated to create longer audio samples with their corresponding transcriptions, designed for text-to-speech (TTS) training where longer sequences are beneficial.
+
+## Dataset Structure
+
+**Configs**:
+* `default`
+
+**Data Files**:
+* Split: `train`
+
+**Dataset Info**:
+* Features:
+  * `audio`: Merged audio file (mono, 22.05kHz)
+  * `transcription`: Concatenated text transcription in Hausa
+  * `speaker_id`: ID of the speaker
+  * `num_segments`: Number of original segments merged
+
+## Usage
+
+To load this dataset in your Python environment using Hugging Face's `datasets` library, use the following code:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("mide7x/hausa_long_voice_dataset")
+```
+
+## Dataset Creation
+
+This dataset was derived from Mozilla Common Voice Hausa collections. The audio files from the same speaker were merged with a small silence between segments. The corresponding transcriptions were concatenated to match the merged audio.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+This dataset helps promote technological inclusion for the Hausa language, which is spoken by over 80 million people primarily in Northern Nigeria, Niger, and other parts of West Africa. The longer audio samples are particularly useful for training more natural-sounding TTS systems.
+
+### Discussion of Biases
+
+The dataset may reflect biases present in the Common Voice collection process, including speaker demographics and sentence selection biases. Additionally, the merging process introduces artificial transitions between naturally spoken segments.
+
+### Citation Information
+
+If you use this dataset in your research, please cite:
+```
+@misc{hausa_long_voice_dataset,
+  author = {Dataset Creator},
+  title = {Hausa Long Voice Dataset},
+  year = {2024},
+  publisher = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/datasets/mide7x/hausa_long_voice_dataset}}
+}
+```

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dataset_info.json

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+{
+  "citation": "",
+  "description": "",
+  "features": {
+    "audio": {
+      "sampling_rate": 22050,
+      "_type": "Audio"
+    },
+    "transcription": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "speaker_id": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "num_segments": {
+      "dtype": "int32",
+      "_type": "Value"
+    }
+  },
+  "homepage": "",
+  "license": ""
+}

state.json

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+}