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## Summary Adds comprehensive Japanese ASR support to FluidAudio with benchmark datasets and CLI commands. ## Changes ### Core Japanese ASR Support - **CtcJaManager.swift** - Japanese CTC transcription manager (actor-based) - **CtcJaModels.swift** - Japanese model loading and management - **ModelNames.swift** - Added Japanese model registry (`parakeetCtcJa`, `CTCJa` enum) - **AsrModels.swift** - Added `.ctcJa` model version (3,072 vocab, 1,024 hidden, blank_id=3072) - **AsrManager.swift** - Added `.ctcJa` case with error directing to `CtcJaManager` ### CLI Commands - **JapaneseAsrBenchmark.swift** (459 lines) - New `ja-benchmark` command - JSUT basic5000 dataset support - Mozilla Common Voice (MCV) test set support - Auto-download capability - CER (Character Error Rate) evaluation - **DownloadCommand.swift** - Added JSUT and MCV Japanese dataset downloads - **TranscribeCommand.swift** - Added `.ctcJa` model version support - **AsrBenchmark.swift** - Added `.ctcJa` switch case ### Dataset Support - **JapaneseDatasetDownloader.swift** (387 lines) - Dataset download and parsing - JSUT basic5000 (5,000 sentences, clean studio recordings) - Mozilla Common Voice Japanese test split - Efficient streaming downloads - Metadata extraction and validation ## Usage ### CLI Commands ```bash # Benchmark on JSUT basic5000 (100 samples) swift run fluidaudiocli ja-benchmark --dataset jsut --samples 100 # Benchmark on Common Voice test (500 samples, auto-download) swift run fluidaudiocli ja-benchmark --dataset cv-test --samples 500 --auto-download # Download datasets swift run fluidaudiocli download --dataset jsut swift run fluidaudiocli download --dataset cv-ja-test ``` ### Swift API ```swift // Load and use Japanese CTC transcription let manager = try await CtcJaManager.load() let text = try manager.transcribe(audioURL: japaneseAudioFile) ``` ## Model Info - **Repo**: `FluidInference/parakeet-ctc-0.6b-ja-coreml` - **Architecture**: 600M parameter CTC-only - **Vocabulary**: 3,072 Japanese SentencePiece tokens + 1 blank (id: 3072) - **Encoder**: 1,024 hidden size - **Expected CER**: 6.5% on JSUT basic5000, 13.3% on MCV 16.1 test ## Testing - ✅ Builds successfully (`swift build`) - ✅ Model loading integration tested - ✅ CLI commands compile and link correctly - ⏳ Runtime benchmark testing pending (requires model download) ## Related - Mobius PR #39: Japanese CTC CoreML conversion (https://github.com/FluidInference/mobius/pull/39) 🤖 Generated with Claude Code <!-- devin-review-badge-begin --> --- <a href="https://app.devin.ai/review/fluidinference/fluidaudio/pull/478" target="_blank"> <picture> <source media="(prefers-color-scheme: dark)" srcset="https://static.devin.ai/assets/gh-open-in-devin-review-dark.svg?v=1"> <img src="https://static.devin.ai/assets/gh-open-in-devin-review-light.svg?v=1" alt="Open with Devin"> </picture> </a> <!-- devin-review-badge-end --> ---------
125 lines
5.1 KiB
Swift
125 lines
5.1 KiB
Swift
#if os(macOS)
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import FluidAudio
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import Foundation
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/// Handler for the 'download' command - downloads benchmark datasets
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enum DownloadCommand {
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private static let logger = AppLogger(category: "Download")
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static func run(arguments: [String]) async {
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var dataset = "all"
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var forceDownload = false
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// Parse arguments
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var i = 0
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while i < arguments.count {
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switch arguments[i] {
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case "--dataset":
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if i + 1 < arguments.count {
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dataset = arguments[i + 1]
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i += 1
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}
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case "--force":
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forceDownload = true
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default:
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logger.warning("Unknown option: \(arguments[i])")
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}
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i += 1
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}
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logger.info("📥 Starting dataset download")
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logger.info(" Dataset: \(dataset)")
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logger.info(" Force download: \(forceDownload ? "enabled" : "disabled")")
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switch dataset.lowercased() {
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case "ami-sdm":
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await DatasetDownloader.downloadAMIDataset(variant: .sdm, force: forceDownload)
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case "ami-ihm":
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await DatasetDownloader.downloadAMIDataset(variant: .ihm, force: forceDownload)
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case "ami-annotations":
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await DatasetDownloader.downloadAMIAnnotations(force: forceDownload)
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case "vad":
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// Default to mini100 for more test data
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await DatasetDownloader.downloadVadDataset(
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force: forceDownload, dataset: "mini100")
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case "vad-mini50":
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await DatasetDownloader.downloadVadDataset(force: forceDownload, dataset: "mini50")
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case "vad-mini100":
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await DatasetDownloader.downloadVadDataset(force: forceDownload, dataset: "mini100")
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case "musan-full":
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await DatasetDownloader.downloadFullMusanDataset(force: forceDownload)
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case "voices-subset":
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await DatasetDownloader.downloadVoicesSubset(force: forceDownload)
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case "librispeech-test-clean":
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let benchmark = ASRBenchmark()
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do {
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try await benchmark.downloadLibriSpeech(
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subset: "test-clean", forceDownload: forceDownload)
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} catch {
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logger.error("Failed to download LibriSpeech test-clean: \(error)")
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exit(1)
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}
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case "librispeech-test-other":
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let benchmark = ASRBenchmark()
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do {
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try await benchmark.downloadLibriSpeech(
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subset: "test-other", forceDownload: forceDownload)
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} catch {
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logger.error("Failed to download LibriSpeech test-other: \(error)")
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exit(1)
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}
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case "earnings22-kws":
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await DatasetDownloader.downloadEarnings22KWS(force: forceDownload)
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case "jsut-basic5000":
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await DatasetDownloader.downloadJSUTBasic5000(force: forceDownload)
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case "cv-corpus-ja-test":
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await DatasetDownloader.downloadCommonVoiceJapanese(
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force: forceDownload, split: .test)
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case "all":
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await DatasetDownloader.downloadAMIDataset(variant: .sdm, force: forceDownload)
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await DatasetDownloader.downloadAMIDataset(variant: .ihm, force: forceDownload)
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await DatasetDownloader.downloadVadDataset(force: forceDownload, dataset: "mini100")
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default:
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logger.error("Unsupported dataset: \(dataset)")
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printUsage()
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exit(1)
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}
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}
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private static func printUsage() {
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logger.info(
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"""
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Download Command Usage:
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fluidaudio download [options]
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Options:
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--dataset <name> Dataset to download (default: all)
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--force Force re-download even if exists
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Available datasets:
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ami-sdm AMI SDM subset
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ami-ihm AMI IHM subset
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ami-annotations AMI annotation files
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vad, vad-mini50, VAD evaluation datasets
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vad-mini100
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musan-full Full MUSAN dataset (~109 hours)
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voices-subset VOiCES small subset (clean/noisy pairs)
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librispeech-test-clean LibriSpeech test-clean subset
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librispeech-test-other LibriSpeech test-other subset
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earnings22-kws Earnings22 keyword spotting dataset
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jsut-basic5000 JSUT Japanese speech dataset (5k utts)
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cv-corpus-ja-test Common Voice Japanese test split
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parakeet-models Parakeet ASR models
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all All diarization datasets
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Examples:
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fluidaudio download --dataset ami-sdm
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fluidaudio download --dataset librispeech-test-clean --force
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fluidaudio download --dataset jsut-basic5000
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fluidaudio download --dataset cv-corpus-ja-test
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"""
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)
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}
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}
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#endif
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