Nowadays, we’re seeing the completion of the open-source TTS models that come back from the local, and the Qwen3-TTS that we’ve recently noticed is how you can pick up voice from the local instead of sending a request to a cloud API and waiting for a response.
When I looked at several podcasts in the format, I was surprised that this degree of freedom is possible locally, without any cost.
For example, the main voice is set and the tone slightly lowered. It is also free to add a different speaker to each corner. The English corner has a clear voice and the Japanese corner has a speeding voice.
In areas where languages are mixed, each language is placed separately in the model. This eliminates the awkwardness of reading English words with Korean pronunciation. Japanese is also the case. It is possible not to break down letters, but to make words and sentences flow naturally.
In detail, there is an endless range of adjustments as to how much the tone is lowered, how much the speed is raised, and how much the gap between the spaces is.But what matters is not a single number, but the feeling that I can control it all with my hands.
If it were a cloud API, there would have been a lot of tokens and restrictions when touching a few parameters, but there is no such thing as local. If you don’t like it, turn it back, and if the tone is strange, change the value and pull it again.
What’s more, it doesn’t cost any of this.When individuals want to create podcasts or audio content with a side project, the entrance barrier is reduced.You don’t have to worry about API costs every time you pick up a voice, and if you fail, you just have to try again.
If you haven’t tried local AI voice synthesis yet, I recommend starting with Qwen3-TTS. The greatest benefit is that it’s much more useful than you think, and above all, it’s free to start.
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