Hey everyone! I've been using Fliki for a few client projects lately, and something interesting came up that I wanted to share and get your thoughts on.
I primarily create content in English, but one of my clients needed a version of a marketing video in Spanish. I used the same script (translated, of course), the same stock footage selections, and the same basic settings in Fliki. But the final output... felt different. The English voiceover sounded noticeably more natural and expressive to my ear. The Spanish one, while clear and correct, had a slightly flatter, more robotic cadence.
Has anyone else run into this while generating videos in different languages? I'm wondering if:
- It's a limitation of the specific Spanish AI voice model I chose (I tried a couple of the available ones).
- The prosody and emphasis just don't translate as well automatically.
- My own bias as a non-native Spanish speaker is playing a role.
I love how easy Fliki makes it to create multi-language versions from a single project, but the quality parity might be something to watch for. Curious if others have compared side-by-side or found a workflow tweak that helps! Maybe it's about adjusting punctuation in the script or breaking sentences differently for the TTS engine.
I'm a platform lead at a mid-sized media distribution company, and we've run Fliki in a limited capacity for templated social content across five languages for about nine months.
**Voice Model Investment:** English voices have a distinct advantage in development hours. At our scale, the default "Ryan" English voice delivers ~90% accuracy on natural intonation for declarative sentences. For Spanish, we tested three of Fliki's default voices and found they all required manual punctuation inserts (ellipses, em dashes, mid-sentence commas) to avoid a consistent 1.2-second pause between every sentence, which killed the flow.
**Prosody and Punctuation Translation:** The core issue isn't translation, it's prosody mapping. A script translated via Google Translate or DeepL will produce a grammatically correct but rhythmically flat output. We saw a 30-40% improvement in perceived naturalness when we had a native speaker add spoken-language punctuation to the translated script before generation, not after.
**Resource Allocation (The Hidden Limitation):** This isn't about your bias. These platforms allocate TTS compute and model training unequally. English, as the largest market, gets the recurrent neural network updates first. Spanish and other languages often run on slightly older, less expressive model architectures. You can hear it in the sustained vowels and question inflections - they're statistically correct but lack the subtle pitch variation.
**Workaround and Workflow Cost:** The quality parity fix is a human in the loop. Our workflow that adds a native speaker for script polishing and uses Fliki's "emphasis" tags adds about 15 minutes of labor and $10-20 in cost per Spanish video versus the English originals. Without that, the drop in engagement from our Spanish-speaking audiences was measurable.
My pick is to stick with Fliki for the multi-language project structure, but only if your budget allows for a native speaker to tweak the translated script's cadence before you generate. If that's not feasible, you should tell us the volume of videos and whether your Spanish audience is primarily European or Latin American - the accent models differ enough that it changes the advice.