SupraLabs released SupraTTS-0.1-Beta, a ~29.6M-parameter text-to-speech model built on the Glow-TTS architecture. The team reports slightly better audio quality than original Glow-TTS at the same size, targeting edge devices and CPU inference. The model is available on Hugging Face with roadmap items including zero-shot voice cloning.
Qwen announced Qwen-Audio-3.1, a fully upgraded audio stack covering ASR, TTS, and Realtime, joined by two new models: TTS-Next for audio creation and ASR-Next for audio understanding. The release spans five models intended to cover understanding, generation, interaction, and creation, with price cuts across the lineup. For practitioners, it consolidates speech recognition, synthesis, and realtime interaction into a single vendor stack.
Qwen announced Qwen-Audio-3.1, a fully upgraded audio stack covering ASR, TTS, and Realtime, joined by two new models: TTS-Next for audio creation and ASR-Next for audio understanding. The release spans five models intended to cover understanding, generation, interaction, and creation, with price cuts across the lineup. For practitioners, it consolidates speech recognition, synthesis, and realtime interaction into a single vendor stack.
Sopro V2 is an open-source text-to-speech model that performs zero-shot voice cloning from 5-20 seconds of reference audio. It supports English, European Portuguese, French, and German, and is designed to run locally on CPU with a simple web UI. It solves the problem of accessible, high-quality voice cloning for developers and hobbyists.
Sopro V2 is an open-source text-to-speech model that performs zero-shot voice cloning from 5-20 seconds of reference audio. It supports English, European Portuguese, French, and German, and is designed to run locally on CPU with a simple web UI. It solves the problem of accessible, high-quality voice cloning for developers and hobbyists.
The creator of Inflect-Nano-v1, which reached #3 in Hugging Face trending base models and #1 in TTS, is building Inflect Nano-v2 with roughly 3.9M parameters. They are running a final blind listening study before releasing the model and Inflect Micro v2 (9.3M parameters) tomorrow.
The creator of Inflect-Nano-v1, which reached #3 in Hugging Face trending base models and #1 in TTS, is building Inflect Nano-v2 with roughly 3.9M parameters. They are running a final blind listening study before releasing the model and Inflect Micro v2 (9.3M parameters) tomorrow.
Tencent released AuK-Flash, the distilled variant of AuK, a 1.5B open-source foundation model unifying speech generation and editing via natural-language instructions. AuK-Flash runs 4-step inference without classifier-free guidance, achieving a 4.5x wall-clock speedup over the full model. Weights are on Hugging Face and ModelScope alongside code, an arXiv report, and a task cookbook, making a single model usable across TTS, editing, enhancement, and separation workflows.
Tencent released AuK-Flash, the distilled variant of AuK, a 1.5B open-source foundation model unifying speech generation and editing via natural-language instructions. AuK-Flash runs 4-step inference without classifier-free guidance, achieving a 4.5x wall-clock speedup over the full model. Weights are on Hugging Face and ModelScope alongside code, an arXiv report, and a task cookbook, making a single model usable across TTS, editing, enhancement, and separation workflows.
The SupraGDN team released SupraGDN-5M on r/LocalLLaMA, a 5M-parameter GatedDeltaNet (GDN1) model trained on 2B tokens. The post claims it competes with other community small models despite training on much less data. It matters to practitioners exploring efficient linear-attention architectures at extreme small scale.
The SupraGDN team released SupraGDN-5M on r/LocalLLaMA, a 5M-parameter GatedDeltaNet (GDN1) model trained on 2B tokens. The post claims it competes with other community small models despite training on much less data. It matters to practitioners exploring efficient linear-attention architectures at extreme small scale.