Blaze Labs · AI Voice
Vietnamese AI voices: Blaze vs ElevenLabs
We put Blaze head-to-head with ElevenLabs — one of the world’s leading AI voice systems — on the hardest thing of all: cloning a Vietnamese voice. Here are the results, with audio clips so you can listen and judge for yourself.
What do we measure?
To keep it fair, we let each system hear a short recording of a person, then asked it to imitate that voice reading a brand-new sentence. We then scored three very down-to-earth questions:
Whether the clone really sounds like the original person.
Whether it reads each Vietnamese word correctly, or mispronounces and invents words.
Whether the voice is smooth and human-like, or robotic and harsh.
And a fourth factor for real-time applications: speed — how long until the first sound of speech.
Listen for yourself
Both read this sentence correctly. The difference is in the timbre.
Notice: the Blaze clone keeps the original person’s timbre, while ElevenLabs reads it correctly but sounds like a different person.
Same story: Blaze stays close to the original, ElevenLabs returns a more “generic” voice.
This is where Vietnamese trips up international models.
Blaze reads it correctly. ElevenLabs mishears it as “bán kinh” — a common kind of Vietnamese mispronunciation for models not specialized in Vietnamese.
Overall results
Across all 50 voices:
| Criterion | Blaze | ElevenLabs | Who leads? |
|---|---|---|---|
| Similarity to original | Clearly higher | Much lower | 🔵 Blaze (wins 48/50 voices) |
| Reading accuracy (errors) | ~3.6% errors | ~8.4% errors | 🔵 Blaze (~2× fewer errors) |
| Naturalness | On par | On par | 🤝 Tie |
In fairness — where is ElevenLabs strong?
We won't hide where ElevenLabs does well:
- Clean, natural audio. ElevenLabs’ flash model scores the highest “naturalness” of all models — it sounds very smooth. In exchange, it’s the least similar to the original voice: you get a nice voice, but not the voice of the person you wanted to clone.
In other words: ElevenLabs gives a voice that’s pleasant and fast; Blaze gives a voice that’s truly that person and reads Vietnamese correctly.
What about Blaze's real-time model?
Good news: Blaze’s real-time model keeps nearly all of the quality of the standard model — still very similar to the original and accurate — while responding fast enough for call centers, virtual assistants, or live content reading. You don’t have to trade much between “fast” and “similar”.
Why does this matter for Vietnamese?
Most well-known AI voice tools were built for English first. For Vietnamese — with its many tones and regional pronunciations — a model “trained for Vietnamese” like Blaze has a real advantage: it preserves the identity of the voice while reducing reading errors. If you do livestream sales, telesales, ad voiceovers, or phone assistants in Vietnamese, this is exactly what makes the difference.
On methodology: 50 real Vietnamese recordings from 50 different people. Each system received the same sample to “clone” the voice, then read a new sentence. “Similarity to original” is measured by matching voice fingerprints; “reading accuracy” by having a speech-recognition system transcribe the output and compare it against the original sentence; “naturalness” by an audio-quality scoring model. The same yardstick applies to both sides. Models compared: Blaze v2.0 and ElevenLabs v3 (and each side’s corresponding real-time model).
The illustrative audio clips are drawn from an internal evaluation dataset, used for research/illustration purposes.