Feature Requests

I know the Record with Others feature is in Beta and the Squadcast recorder allowed for scheduling recording sessions. I would love to see that feature added to the Beta because having to send the link minutes before recording is problematic.

gm@Hi. I'm a blind user of Descript and formerly squadcast. I do remote recordings and interviews for my radio station. In squadcast you had keyboard shortcuts to make using the control buttons quicker and easier. In the new Rooms section there are none. Can you pleas reinstate keyboard shortcuts for important buttons like record and stop recording, etc.

Can you add a feature where I can use an image as the background to the video when I am in a meeting?

Being able to clone my voice so it sounds exactly like me with the right pitch, animation, hype, speed by using other videos I have recorded live. Think 11Labs level. At the moment it sounds nothing like me.

Hello Descript team, First of all, I want to say thank you for the impressive work you’ve done with AI voices—there’s already a great level of natural intonation and quality. I would love to suggest a feature that could make AI voice generation even more powerful and flexible: It would be incredibly useful to have more direct control over the emotional tone of the AI voice. For example, the ability to specify whether a voice should sound calm, neutral, angry, or expressive—either across the entire script or in specific sections. Ideally, this could include: Global tone settings (e.g., calm, friendly, serious) Section-based emotional control within the script (e.g., slightly angry → angry → very angry) The ability to fine-tune intensity levels of emotions Integration with Underlord or voice settings when selecting a speaker This would open up much more creative storytelling and allow users to better match tone with context, especially in narrative or dynamic content. Thanks again for the amazing tools you’re building—I’d love to see this kind of emotional control added in the future.

Hello Descript team, I’d like to suggest a feature that would significantly improve workflows for creating AI-generated meditations. When producing guided meditations, a large part of the work involves manually adjusting pacing—adding pauses between sentences (and within the sentences), spacing between sections, and sometimes inserting breathing cues or moments of silence. This is quite time-consuming, especially since the default AI voice delivery is often too fast for meditation purposes. It would be incredibly helpful if Underlord could learn from or reference existing projects as templates. For example, I’d like to be able to say: “Use this previous meditation as a template for pacing, pauses, and breathing.” Based on that, Underlord could automatically: Apply appropriate pauses between sentences and sections Adjust pacing to a slower, more suitable meditation speed Insert breathing spaces or timing patterns similar to the reference meditation Maintain a consistent structure across multiple meditation projects This would make it much easier to standardize high-quality meditation experiences and dramatically reduce manual editing time. Overall, the goal is to reuse the structure and timing from existing meditations to quickly generate new ones with similar flow and rhythm. Thank you for all the great tools you’re building—this kind of feature would be a huge improvement for creators working with long-form, timing-sensitive audio like meditations.

Love Descript - just wish timeline navigation was a bit smoother - one thing particularlytt is when i want to export a selection from a longer script - having to scroll select the text is clunky if its a long section - needs to be a view mode where i can select blocks of text more easily

When using the gap shortening or word gap editing tools, cuts are applied automatically based on duration thresholds. However, the resulting edit boundaries don't always align perfectly with the natural audio waveform — there are cases where a cut lands mid-breath, mid-consonant, or at a non-zero crossing, causing audible pops or unnatural transitions. Request: Allow users (and the AI agent) to automatically fine-tune individual cut boundaries by dragging them automatically to align with waveform zero-crossings or natural silence points in the audio. Ideally this would include: Waveform-snapping when dragging edit boundaries, so cuts snap to the nearest zero-crossing or silence Per-cut adjustment in the timeline so individual gaps can be nudged frame-by-frame or sample-by-sample Agent support so the AI can automatically detect and adjust cuts that don't land on clean audio boundaries This would significantly improve audio quality for podcasts, interviews, and any heavily edited spoken-word content.

When exploring open feedback communities, patterns begin to emerge in how users share ideas and experiences. A discussion like exotic pet relocation services canada https://pearllemonpets.ca/services/exotic-pet-relocation/ may seem niche at first glance, yet it reflects how diverse topics can surface in collaborative spaces. These platforms are not limited to one industry but instead act as hubs where practical concerns meet real user perspectives. In many feedback-driven environments, users are not trying to sell something. Instead, they are sharing real challenges, suggestions, and observations based on direct experience. This creates a more authentic layer of content compared to structured blogs or commercial pages. On platforms such as Descript feedback boards, the focus is often on improvement. Users submit feature requests, highlight usability issues, and discuss workflows openly. The tone remains conversational, making it easier for others to relate and contribute. Interestingly, topics can range from technical editing tools to completely different services. This mix shows how users bring their broader experiences into a single space. It’s not uncommon to find discussions that connect unrelated industries through shared problem-solving approaches. Another key aspect is transparency. People talk about what works and what doesn’t without the pressure of marketing language. This honesty builds trust and encourages deeper engagement among contributors. These discussions often reveal recurring needs. Whether it’s about improving software functionality or navigating complex services, similar concerns appear repeatedly. Over time, this helps shape better solutions and more refined tools. Feedback platforms also encourage structured thinking. Users present ideas clearly, often outlining problems and suggesting improvements. This creates a collaborative environment where innovation grows organically. The absence of promotional intent makes the content more valuable. Readers can focus on insights rather than filtering through advertisements. This leads to a more meaningful exchange of information. Another interesting element is adaptability. As new trends emerge, discussions evolve quickly. Users bring fresh perspectives that reflect current needs and expectations. In such environments, even highly specific topics find relevance. They become part of a larger conversation about efficiency, usability, and real-world application. Ultimately, feedback communities serve as living ecosystems of ideas. They connect people from different backgrounds through shared experiences. And in doing so, they highlight how diverse discussions can coexist and contribute to collective learning.