Qlerqly/griot-nano-1-kenlm

Griot Nano 1 Multilingual KenLM

This is the multilingual 3-gram KenLM language model for Qlerqly/griot-nano-1. It covers Akan, Dagbani, Ewe, Ghanaian English, and Ga using the same normalized transcript domain as the Griot Nano 1 acoustic model.

Recommended decoding configuration

For best contextual accuracy, we recommend KenLM-assisted CTC beam search with Griot Nano 1. It improves the decoder's preference for plausible character and word sequences, particularly around ambiguous acoustics and word boundaries.

KenLM is a compact n-gram model rather than a second neural network. This keeps memory and compute overhead low relative to neural language-model rescoring. Greedy CTC remains the lowest-latency option.

Suggested starting settings:

• —Beam width: 25
• —LM weight (alpha): 0.5
• —Word insertion bonus (beta): 1.0

These are starting points rather than universal optima; tune them on a held-out set for your target language and domain.

Results Vs Greedy and Beam search decode

Download and use

uvx --from huggingface-hub hf download Qlerqly/griot-nano-1-kenlm \
  --local-dir griot-nano-1-kenlm

uv run --with-requirements requirements-kenlm.txt python inference.py \
  --model-dir . --audio recording.wav \
  --kenlm ../griot-nano-1-kenlm/multilingual.arpa --beam-width 25

The acoustic-model repositories provide requirements-kenlm.txt and the KenLM-enabled inference script.

Model details

• —Format: ARPA
• —Order: 3-gram
• —Size: 214.2 MiB
• —SHA-256: c017eaaa575a0bb0dfc30ab74953a95f9e11939ca7d0a034eed3c446ded328f6
• —Quantized: no

Training data and license

This language model was derived from normalized transcripts associated with the Griot Nano 1 training sources. See ATTRIBUTIONS.md for the complete source, creator, and license record.