Datasets:

hadamard-2
/

alffa-amharic-v2

language:
  - am
tags:
  - audio
  - automatic-speech-recognition
license: mit
task_categories:
  - automatic-speech-recognition
pretty_name: ALFFA Amharic Speech Corpus (v2)
size_categories:
  - 10K<n<100K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
dataset_info:
  features:
    - name: id
      dtype: string
    - name: speaker_id
      dtype: string
    - name: transcription
      dtype: string
    - name: language
      dtype: string
    - name: gender
      dtype: string
    - name: audio
      dtype:
        audio:
          sampling_rate: 16000
  splits:
    - name: train
      num_bytes: 2310241147.75
      num_examples: 10875
    - name: test
      num_bytes: 84301800
      num_examples: 359
  download_size: 1982915180
  dataset_size: 2394542947.75

ALFFA Amharic Speech Corpus (v2)

Read speech corpus for Amharic (አማርኛ) automatic speech recognition. Converted from the original ALFFA project and restructured to match the google/waxalnlp schema for interoperability.

This is a restructured version of hadamard-2/alffa-amharic.

Changes from v1

utterance_id renamed to id
transcript renamed to transcription
speaker_id set to "unknown" — the original ALFFA Kaldi files shipped with utt2spk mapping each utterance to itself, providing no reliable speaker identity information
language column added, filled with "amh" (ISO 639-2 for Amharic)
gender column added, filled with "unknown" — not available in the original corpus
split column dropped — redundant with the HuggingFace dataset split structure
Schema metadata updated to explicitly declare sampling_rate: 16000 on the audio column

Dataset Structure

{
    'id': 'tr_10000_tr097082',
    'speaker_id': 'unknown',
    'transcription': 'ይህ አማርኛ ጽሑፍ ነው',
    'language': 'amh',
    'gender': 'unknown',
    'audio': {'bytes': ..., 'path': 'tr_10000_tr097082.wav'},  # 16kHz mono
}

Usage

from datasets import load_dataset

dataset = load_dataset("hadamard-2/alffa-amharic-v2")
example = dataset['train'][0]
print(example['transcription'])
audio_array = example['audio']['array']
sampling_rate = example['audio']['sampling_rate']

Splits

Train: 10,875 utterances (~20 hours)
Test: 359 utterances (~2 hours)

Citation

@article{tachbelie2014,
    Author = {Martha Tachbelie and Solomon Teferra Abate and Laurent Besacier},
    Journal = {Speech Communication},
    Publisher = {Elsevier},
    Title = {Using different acoustic, lexical and language modeling units for ASR of an under-resourced language - Amharic},
    Volume = {56},
    Year = {2014}
}

License

MIT License (from OpenSLR)