{ "schema_version": 1, "title": "Apple SpeechAnalyzer vs whisper.cpp on Mac", "canonical_url": "https://iravoice.com/research/apple-speechanalyzer-vs-whisper-cpp-mac", "published_at": "2026-07-26", "license": "CC BY 4.0", "source_repository": "https://github.com/mvplab-ai/mac-asr-benchmark", "source_release": "https://github.com/mvplab-ai/mac-asr-benchmark/releases/tag/v1.0.0", "dataset_mirror": "https://huggingface.co/datasets/researchaudio/apple-speechanalyzer-vs-whisper-cpp-mac", "source_commit": "81ecbb9582d0990827c76be0e685124d2be651c8", "source_visibility": "private", "manifest_sha256": "171639597cda2a98311fab77b169aa7086e95321f402b50c1f93b597dbd7fc36", "dataset": { "archive_md5": "32fa31d27d2e1cad72775fee3f4849a9", "license": "CC BY 4.0", "name": "LibriSpeech ASR corpus", "selection": "One clip from each of the 40 test-clean speakers. For each speaker, choose the first clip in lexicographic transcript order with 8-20 reference words and 4-10 seconds of audio. The source split contains 20 female and 20 male speakers.", "source_url": "https://www.openslr.org/12", "split": "test-clean" }, "environment": { "hardware_model": "Mac17,7", "operating_system": "Version 26.5 (Build 25F71)", "physical_memory_bytes": 137438953472, "processor": "Apple M5 Max" }, "protocol": { "engines": "The benchmark invokes IraVoice's production Apple SpeechAnalyzer and whisper.cpp server adapters.", "pacing": "The same 16 kHz mono audio is fed in 100 ms chunks at real-time pace.", "accuracy": "WER and CER are micro-averaged after case, punctuation, Unicode-width, and diacritic normalization. Digits are not rewritten as words.", "latency": "Post-speech latency starts after the final audio chunk is appended and ends when the complete raw transcript returns. Formatting and insertion are excluded.", "warmup": "The first clip is run once as an unreported warmup before all 40 clips are measured.", "repetitions": "Two complete final-commit runs were recorded per engine on the same machine and OS." }, "direct_answer": "On this 40-speaker LibriSpeech test-clean snapshot, Apple SpeechAnalyzer produced 1.98% WER and whisper.cpp small.en produced 4.28% WER. Repeated post-speech latency overlapped: Apple median 125-132 ms and p95 194-201 ms; whisper.cpp median 122-125 ms and p95 152-161 ms.", "limitations": [ "This is clean read audiobook speech, not spontaneous desktop dictation.", "The 40 clips are a deterministic speaker-balanced snapshot, not the complete LibriSpeech test-clean split.", "The results cover one Apple M5 Max running macOS 26.5 and one whisper.cpp model.", "The results do not establish noisy-speech, accented-speech, multilingual, accessibility, or population-wide performance.", "Apple SpeechAnalyzer is streaming while this whisper.cpp server path is batch; only the disclosed post-speech interval is compared.", "IraVoice publishes the study and ships the Apple engine. The production application source remains proprietary; the public repository contains the complete artifacts, manifest, checksums, and scoring verifier rather than the runner source." ], "engine_summaries": [ { "engine_id": "apple", "engine_name": "Apple SpeechAnalyzer", "model_label": "macOS SpeechAnalyzer progressiveTranscription", "streaming": true, "run_count": 2, "successful_clips_per_run": 40, "word_error_rate_percent": 1.98, "character_error_rate_percent": 1.02, "post_speech_latency_median_ms_range": [ 125, 132 ], "post_speech_latency_p95_ms_range": [ 194, 201 ] }, { "engine_id": "whisper", "engine_name": "whisper.cpp server", "model_label": "whisper.cpp 1.8.4 · ggml-small.en", "streaming": false, "run_count": 2, "successful_clips_per_run": 40, "word_error_rate_percent": 4.28, "character_error_rate_percent": 1.79, "post_speech_latency_median_ms_range": [ 122, 125 ], "post_speech_latency_p95_ms_range": [ 152, 161 ] } ], "runs": [ { "run_id": "apple-r1", "chunk_milliseconds": 100, "clips": [ { "audio_duration_ms": 4905, "begin_ms": 39, "category": "clean-read-speech", "feed_ms": 5163, "hypothesis": "He began a confused complaint against the wizard who had vanished behind the curtain on the left.", "id": "61-70968-0000", "post_speech_ms": 127, "reference": "HE BEGAN A CONFUSED COMPLAINT AGAINST THE WIZARD WHO HAD VANISHED BEHIND THE CURTAIN ON THE LEFT", "score": { "character_edits": { "deletions": 0, "insertions": 0, "substitutions": 0 }, "character_error_rate": 0, "hypothesis_characters": 80, "hypothesis_words": 17, "normalized_hypothesis": "he began a confused complaint against the wizard who had vanished behind the curtain on the left", "normalized_reference": "he began a confused complaint against the wizard who had vanished behind the curtain on the left", "reference_characters": 80, "reference_words": 17, "word_edits": { "deletions": 0, "insertions": 0, "substitutions": 0 }, "word_error_rate": 0 }, "sex": "M", "speaker": "61", "wall_clock_ms": 5330 }, { "audio_duration_ms": 8460, "begin_ms": 45, "category": "clean-read-speech", "feed_ms": 8900, "hypothesis": "Also, a popular contrivance whereby love making may be suspended, but not stopped during the picnic season.", "id": "121-121726-0000", "post_speech_ms": 154, "reference": "ALSO A POPULAR CONTRIVANCE WHEREBY LOVE MAKING MAY BE SUSPENDED BUT NOT STOPPED DURING THE PICNIC SEASON", "score": { "character_edits": { "deletions": 0, "insertions": 0, "substitutions": 0 }, "character_error_rate": 0, "hypothesis_characters": 88, "hypothesis_words": 17, "normalized_hypothesis": "also a popular contrivance whereby love making may be suspended but not stopped during the picnic season", "normalized_reference": "also a popular contrivance whereby love making may be suspended but not stopped during the picnic season", "reference_characters": 88, "reference_words": 17, "word_edits": { "deletions": 0, "insertions": 0, "substitutions": 0 }, "word_error_rate": 0 }, "sex": "F", "speaker": "121", "wall_clock_ms": 9098 }, { "audio_duration_ms": 6510, "begin_ms": 41, "category": "clean-read-speech", "feed_ms": 6842, "hypothesis": "Oh, she's always at the piano said van. 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