LambdaAudio v6

LambdaAudio v6 is a Japanese automatic speech recognition (ASR) model that converts speech into Japanese text. It combines a Zipformer audio encoder with an LFM2.5 language decoder, both adapted to Japanese audio or transcripts before joint training.

On Japanese subset of Google FLEURS ASR benchmark, it achieves a character error rate (CER) close to Whisper large-v3-turbo (6.05% vs. 5.83%) while transcribing audio 2.3× faster.

Model details

Field Value
Developer Keisuke Miyamoto
Task / language Speech-to-text / Japanese (ja)
Model type Encoder-decoder with an audio adapter and gated cross-attention
Model size 350M parameters
Audio encoder KeisukeMiyamoto/zipformer-cpt
Text decoder / tokenizer KeisukeMiyamoto/lfm2.5-230m-cpt
Input 16 kHz audio, up to 30 seconds per segment
Output Japanese transcription text
Audio feature interval 20 ms after the encoder; 40 ms after the adapter

Architecture

The Zipformer encoder extracts features from 16 kHz audio. An audio adapter reduces the sequence length and projects these features into the decoder's hidden dimension. Gated cross-attention in the LFM2 full-attention blocks lets the decoder use audio features to predict the next text token.

LambdaAudio architecture: Zipformer encoder, audio adapter, and LFM2 decoder with gated cross-attention

Training data

Stage Dataset Sources and labels
Encoder continued pretraining Whisper Cluster Audio Internet Archive, publicly available podcasts, and radio; 500 cluster labels derived from Whisper large-v3-turbo encoder features
Decoder continued pretraining Japanese Audio Transcripts Japanese transcripts from NHK archives and technology podcasts
Joint ASR training Lambda Audio Corpus NHK archives, technology podcasts, and ReazonSpeech

Benchmarks

Each cell shows CER (%) / total transcription time (seconds). Lower values are better.

Model ReazonSpeech Common Voice 25 Japanese FLEURS Japanese
LambdaAudio v6 10.75 / 121.55 23.87 / 167.84 6.05 / 20.75
Whisper large-v3-turbo 11.42 / 354.04 26.40 / 592.25 5.83 / 47.82
Kotoba-Whisper v2.2 11.70 / 322.53 22.89 / 541.39 7.35 / 46.15
ReazonSpeech wav2vec2 14.01 / 49.35 31.43 / 68.22 15.04 / 9.22
Parakeet tdt_ctc-0.6b-ja 10.62 / 55.10 19.99 / 82.28 5.94 / 9.74
Cohere Transcribe 03-2026 6.45 / 176.00 21.58 / 227.42 4.36 / 30.77

ReazonSpeech

CER and transcription time on ReazonSpeech test

Common Voice 25 Japanese

CER and transcription time on Common Voice 25 Japanese test

FLEURS Japanese

CER and transcription time on FLEURS Japanese test

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Evaluation results