Parler-TTS, an open-source text-to-speech library designed for generating high-quality speech, has not seen any new commits since August 19, 2024. The project, backed by research from Stability AI and Edinburgh University, aims to provide customizable speech synthesis through user-defined parameters.
Recent issues and pull requests indicate a community-driven effort to expand language support and improve model performance. Issues like #116 and #115 reflect user demand for Italian and Chinese language support, while #112 highlights concerns over voice consistency. Pull requests such as #110 address audio generation artifacts, suggesting ongoing efforts to refine the TTS output quality.
Yoach Lacombe (ylacombe)
Sanchit Gandhi (sanchit-gandhi)
UncleCode (unclecode)
Eustlb
Sang Nguyen (sang-nguyen-ts)
The team has concentrated on documentation enhancements and bug fixes, with a collaborative approach evident in co-authored commits.
| Timespan | Opened | Closed | Comments | Labeled | Milestones |
|---|---|---|---|---|---|
| 7 Days | 7 | 1 | 5 | 7 | 1 |
| 30 Days | 20 | 5 | 42 | 20 | 1 |
| 90 Days | 43 | 17 | 106 | 43 | 1 |
| All Time | 80 | 22 | - | - | - |
Like all software activity quantification, these numbers are imperfect but sometimes useful. Comments, Labels, and Milestones refer to those issues opened in the timespan in question.
| Developer | Avatar | Branches | PRs | Commits | Files | Changes |
|---|---|---|---|---|---|---|
| Yoach Lacombe |  |
1 | 4/5/0 | 5 | 19 | 2380 |
| eustlb |  |
1 | 0/1/0 | 1 | 13 | 922 |
| UncleCode |  |
1 | 1/1/0 | 1 | 1 | 2 |
| Akash Gupta (Guppy16) | 0 | 1/0/0 | 0 | 0 | 0 | |
| Artem Bolgar (Artyom17) | 0 | 0/0/1 | 0 | 0 | 0 | |
| Ashwin Sankar (AshwinSankar17) | 0 | 1/0/1 | 0 | 0 | 0 | |
| Sanchit Gandhi (sanchit-gandhi) | 0 | 0/0/1 | 0 | 0 | 0 | |
| tsdocode (sang-nguyen-ts) | 0 | 1/0/2 | 0 | 0 | 0 | |
| edwixx (anurag12-webster) | 0 | 1/0/0 | 0 | 0 | 0 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
The GitHub repository for Parler-TTS has seen active engagement, with 58 open issues currently being discussed. Recent activity includes a mix of feature requests, bug reports, and inquiries about model usage, indicating a vibrant community that is both utilizing and contributing to the project. Notably, there are several issues related to language support and model performance, suggesting ongoing interest in expanding the capabilities of the TTS system.
A significant theme among the recent issues is the request for support for various languages (e.g., Italian, Chinese) and improvements in voice consistency across different generations. Additionally, users are seeking guidance on fine-tuning models with specific datasets and addressing technical errors encountered during training or inference. The presence of multiple issues regarding audio quality and generation speed highlights areas where users are experiencing challenges that could impact their overall satisfaction with the tool.
Issue #119: Substitute different Audio codec and Text encoder?
Issue #117: Documentation references to facebook/parler_tts-small
Issue #116: How to use Italian language?
Issue #115: Hope to support Chinese.
Issue #112: Speaker voice is not consistent across different generation
Issue #111: Asking for GPU to finetune large model
Issue #100: Error on fine tuning
Issue #99: GGML implementation when?
Issue #97: Some questions to prepare multilinguality training from scratch
Issue #95: Any list of all 36 voices?
This selection of issues illustrates a diverse range of user needs, from technical troubleshooting to feature enhancement requests, reflecting both the complexity of TTS technology and the community's eagerness to expand its capabilities.
The repository huggingface/parler-tts currently has 4 open pull requests and a substantial history of closed pull requests, totaling 34. The recent activity indicates ongoing development focused on bug fixes, feature enhancements, and optimizations for the text-to-speech (TTS) functionalities.
PR #110: Bugfix: Delay pattern mask is applied twice
Created 8 days ago. This PR addresses multiple issues related to the application of delay masks in the TTS generation process, which could lead to audio artifacts. It also includes an example notebook for voice enrollment, enhancing audio consistency. Notably, there are discussions about whether similar fixes should be applied to another class, indicating potential oversight in code coverage.
PR #103: Trivia typo fix in comments
Created 10 days ago. A minor contribution aimed at correcting typos in the comments of the training script. The contributor expresses a desire for guidance on adding GGML support, highlighting a learning curve for newcomers.
PR #72: Fixed some errors to make it easier for first-time users
Created 71 days ago. This PR aims to improve user experience by addressing common issues faced by new users when using the official codebase. It suggests refinements to model initialization scripts based on user feedback.
PR #60: [training] apply save_total_limit to push
Created 86 days ago. This PR enhances the training configuration by ensuring that the save_total_limit parameter applies not only locally but also when pushing models to the Hugging Face Hub. It includes testing details and demonstrates practical application through a specific training configuration.
PR #118: Fix shape error in si-sdr function
Closed 1 day ago without merging. This PR attempted to fix a shape error in a function but was not merged.
PR #113: Fix reduce torch compile long warmup
Closed 5 days ago without merging. It aimed to address performance issues related to warm-up times during model compilation but did not achieve consensus for merging.
PR #108: Update training guide colab
Merged 9 days ago. This PR updated documentation related to training guides, reflecting changes in usage and improving clarity for users.
PR #102: Update training guide
Merged 9 days ago. Similar to PR #108, this update included necessary adjustments for versioning and configurations relevant to training processes.
The pull requests reflect several key themes in the ongoing development of the Parler-TTS project:
Bug Fixes and Enhancements: A significant portion of both open and closed pull requests focus on bug fixes, particularly concerning audio generation artifacts and user experience improvements. For instance, PR #110 addresses critical bugs that could degrade audio quality during TTS generation, while PR #72 aims to streamline the onboarding process for new users by fixing common errors encountered with initial setups.
Documentation Improvements: Several recent pull requests have concentrated on enhancing documentation and training guides (e.g., PRs #108 and #102). This is crucial as it not only aids current contributors but also attracts new users who may be intimidated by complex setups or unclear instructions.
Performance Optimizations: There is a clear trend towards optimizing performance, particularly regarding model compilation and inference speed (e.g., PRs #60 and #113). These optimizations are essential given the resource-intensive nature of TTS models and the increasing demand for real-time applications.
Community Engagement: The discussions within pull requests often indicate a collaborative environment where contributors seek feedback from maintainers (e.g., Akash Gupta's inquiries in PR #110). However, there are also signs of potential bottlenecks in review processes, as seen with several unmerged or closed PRs that may benefit from more timely feedback.
Diversity of Contributions: The range of contributions—from trivial typo fixes (PR #103) to significant architectural changes (e.g., previous PRs related to attention mechanisms)—demonstrates an active community willing to engage with various aspects of the codebase. However, it also highlights a need for clearer guidelines on contribution expectations and areas where help is most needed.
Old Pull Requests and Merge Activity: While there is ongoing activity with new pull requests being created regularly, some older pull requests remain unmerged or have been closed without resolution (e.g., PRs like #84 and #59). This could indicate either a lack of resources for thorough reviews or shifting priorities within the project that may leave certain contributions overlooked.
In conclusion, while Parler-TTS is progressing well with active contributions focused on bug fixes, documentation improvements, and performance enhancements, there remains an opportunity to improve engagement with contributors and streamline the review process for incoming pull requests. Addressing these areas could further enhance the project's growth and usability within the TTS community.
Yoach Lacombe (ylacombe)
Sanchit Gandhi (sanchit-gandhi)
UncleCode (unclecode)
Eustlb
Sang Nguyen (sang-nguyen-ts)
Other Members (AshwinSankar17, Guppy16, anurag12-webster, Artyom17)
The development team is currently engaged in a productive cycle of documentation enhancement, bug fixing, and feature optimization. The collaborative nature of their work suggests a healthy team dynamic focused on improving both the functionality and usability of the Parler-TTS project.
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