FAMILIAR VS ELEVENLABS · TWO PAIRED STUDIES · AUGUST 2026

Tested more accurate than ElevenLabs.

Even just on voice, dubbing is finally good.

01 · THE VOICE +27.8%

Familiar sounds 27.8% more like the real speakertheir Dubbing v1 · 418 paired dubs · 11 languages

CLOSER IN ALL 11 LANGUAGES TESTED

02 · THE TRANSLATION −54.7%

Familiar made 54.7% fewer important translation errorsvs their newest Dubbing v2 (Alpha) · 111 paired dubs · 3 languages

ElevenLabs64

Familiar29

03 · THE LAUGHS +221%

ElevenLabs got laughs and reactions 221% more wrong in loudnessshape correlation +28.2% for Familiar (0.960 vs 0.749) · 18 clips / 54 comparisons

ElevenLabs3.32 dB

Familiar1.04 dB

04 · THE SCENE

Keeps the laughter, the music and bass, the ambience of the city, train, or party.

+270% more background-sound error · ElevenLabsthe noise bed: music, effects, and room ambience · same clips

ElevenLabs11.92 dB

Familiar3.22 dB

38/38 clips completed — ElevenLabs rejected the one under 11 seconds $4.98 per finished minute with translation, voice, scene audio, and lipsync included; ElevenLabs quoted $3 at checkout, audio only

ElevenLabs Dubbing v2 (Alpha) evidence ElevenLabs Dubbing v1 evidence

ELEVENLABS DUBBING V1 · 11-LANGUAGE BREAKDOWN · CLICK TO LISTEN

Hear the difference on ElevenLabs’ Dubbing v1

Loading paired benchmark records and listening examples…

ELEVENLABS DUBBING V2 (ALPHA) · THEIR NEWEST PRODUCT

Coverage and workflow failures are part of the result.

PRODUCT COVERAGE Familiar 38/38 · ElevenLabs Dubbing v2 (Alpha) 37/38

COST-CONTROLLED THREE-LANGUAGE SUBSET Mandarin Chinese · Spanish · Japanese

ElevenLabs quoted $3 per dubbed minute per language at checkout (August 5, 2026), audio only. Familiar is $4.98 per finished minute per language with translation, voice, scene audio, and lipsync included.

DUBBING V2 (ALPHA) OUTPUTS All 111 paired comparisons scored

222 final audio files, matched and transcribed.

SHORT CLIPS REJECTED10.94-second Jimmy Yang clip cannot be dubbed.

Familiar completed it; ElevenLabs enforces an 11-second minimum.

ITEMS PER BATCHA catalogue job must be split almost immediately.

4 videos into 6 languages is already 24 outputs.

CONCURRENT REQUESTSMulti-video, multi-language work waits in waves.

Ten videos into ten languages creates 100 requests: at least four waves before generation time is counted.

OBSERVED CATALOGUE WORKFLOWSlow and tedious at creator-catalogue scale.

The Spanish pass alone was slow; larger catalogues can require hours of manual batching.

Selection fairness. Korean, our strongest native-review language, was not selected.

111 PAIRED FINAL-AUDIO OUTPUTS

Final-audio results: Familiar vs ElevenLabs Dubbing v2 (Alpha)

95% intervals resample source clips.

ElevenLabs: 270% more background-sound error 11.92 vs 3.22 dB MAE · Familiar 73.0% lower · paired 95% CI excludes zero

ElevenLabs: 221% more laughter/reaction loudness error 3.32 vs 1.04 dB · Familiar 68.8% lower · 18 clips / 54 comparisons

28.2% higher laughter/reaction shape correlation 0.960 vs 0.749 · 18 clips / 54 paired comparisons · paired 95% CI excludes zero

ElevenLabs: 121% more important spoken translation errors 64 vs 29 · Familiar 54.7% lower · 111 paired final-audio comparisons

ElevenLabs: 56.5% more finished dubs with any important meaning problem 36 vs 23 · Familiar 36.1% lower · paired 95% CI excludes zero

+3.5% point estimate speaker-resemblance median 0.485 vs 0.469 SIM-o · sample was not large enough to prove a real lead

No clear winner predicted voice naturalness 2.490 vs 2.494 UTMOS · uncertainty is broad

38/38 vs 37/38 source-clip coverage ElevenLabs rejected the 10.94-second clip under its 11-second minimum.

How meaning was checked: each finished dub was transcribed with Scribe v2, then manually reviewed against the same approved target meaning; valid paraphrases accepted.

Observed in the ElevenLabs website Dubbing v2 (Alpha) workflow on August 5, 2026. Product limits may change.

ELEVENLABS DUBBING V1 · 38 CLIPS · 11 LANGUAGES · 418 PAIRED TRIALS

Final-audio results: Familiar vs ElevenLabs Dubbing v1

Higher-is-better measures lead with Familiar's gain; lower-is-better measures lead with how much more error ElevenLabs produced.

More recognizable voices

Source-speaker resemblance was higher in every target language.

Fewer problems in the final spoken audio

Review found 132 individual issues in Familiar outputs and 258 in ElevenLabs outputs.

The scene survived the dub

Laughter shapes, the noise bed, and transient timing stayed closer to the source.

PLAIN-LANGUAGE METRIC GUIDE