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.
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.
These are starting points rather than universal optima; tune them on a held-out
set for your target language and domain.
1uvx --from huggingface-hub hf download Qlerqly/griot-nano-1-kenlm \
2 --local-dir griot-nano-1-kenlm
3
4uv run --with-requirements requirements-kenlm.txt python inference.py \
5 --model-dir . --audio recording.wav \
6 --kenlm ../griot-nano-1-kenlm/multilingual.arpa --beam-width 25
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.
