# Interspeech 2026 review form > Simulate Interspeech-style reviews: confidence, appropriateness, novelty, technical correctness, clarity, reproducibility and references on 1–4, a six-level overall recommendation and detailed comments for the authors. - Venue: Interspeech (Annual Conference of the International Speech Communication Association) - Form status: modeled, not official. Interspeech's CMT review form is not public. The criteria list follows a paper that analysed Interspeech 2019 review data and the official long-paper criteria; a few labels come from a public 2023 Show & Tell review. Most scale labels are ours. - Official source: https://www.isca-archive.org/interspeech_2020/stappen20_interspeech.pdf - Overall score: Overall Recommendation, 1–6 - Rough acceptance bar (our simulation): mean ≥ 3.75 - Web page: https://reviewpaper.ai/venues/interspeech ## How reviewers read the paper Interspeech reviews (double-blind, CMT) rate appropriateness, novelty, technical correctness, clarity, reproducibility and references, give an overall recommendation and write detailed comments (overall impression, novelty, clarity, what to improve) that justify the scores. Long papers are judged on depth of contribution, originality, technical correctness, clarity, quality of references and potential long-term impact. Meta-reviewers consolidate the reviews. - Detailed comments must justify every score (at least ~120 words). - Do not penalize non-native English as long as the content is clear. - Constructive and specific; name missing references. **Where the bar sits.** Interspeech accepts roughly 50% of regular papers (official special-sessions call); the new long-paper track targets below 30%. On this 1–6 scale a mean of ≥ 3.75 (Weak Accept or better) is a rough proxy for acceptance. ## Reviewer form, field by field ### 1. Appropriateness Of Topic For The Conference Type: score, 1–4. Fit to speech science and technology. Explain a 1 or 2 in the comments. - **4**: Very appropriate - **3**: Appropriate - **2**: Marginally appropriate - **1**: Not appropriate ### 2. Novelty And Originality Type: score, 1–4. Originality relative to prior speech/audio work; cite the prior work for low scores. - **4**: Very novel and/or innovative - **3**: Novel - **2**: Somewhat incremental - **1**: Not novel ### 3. Technical Correctness Type: score, 1–4. Soundness of methods, experiments and statistics. - **4**: Technically sound - **3**: Mostly sound, minor issues - **2**: Some significant issues - **1**: Major technical flaws ### 4. Clarity Of Presentation Type: score, 1–4. The English need not be flawless; judge whether the content is understandable. - **4**: Very clear - **3**: Clear enough, could benefit from some revision - **2**: Difficult to follow in places - **1**: Unclear ### 5. Reproducibility Type: score, 1–4. Data, setup, hyperparameters and code availability. - **4**: Easily reproducible - **3**: Mostly reproducible - **2**: Hard to reproduce - **1**: Not reproducible ### 6. Quality Of References Type: score, 1–4. References should be peer-reviewed where possible; name missing work. - **4**: Excellent - **3**: Adequate - **2**: Some important references missing - **1**: Inadequate ### 7. Overall Recommendation Type: score, 1–6. Overall recommendation, consistent with the sub-scores. - **6**: Definite Accept: I feel strongly that this paper must be accepted - **5**: Accept - **4**: Weak Accept - **3**: Weak Reject - **2**: Reject - **1**: Definite Reject ### 8. Strengths Type: list of points. Part of "Detailed Comments For Authors". Overall impression, novelty/originality and innovation, with specifics. ### 9. Weaknesses And Suggested Improvements Type: list of points. Part of "Detailed Comments For Authors". What to improve, with specifics. Together with the strengths, at least 120 words, justifying the scores. ### 10. Reviewer Confidence Type: score, 1–4. Selecting a value confirms you are competent to review the paper. - **4**: Very Confident - I consider myself an expert in this area - **3**: Confident - I am familiar with this area - **2**: Somewhat confident - I have some familiarity with this area - **1**: Not confident - this area is outside my expertise ## Area chair meta-review Interspeech meta-reviewers consolidate reviews for the TPC; the form is not public. Recommendation options: Accept · Reject ## Interspeech author checklist 1. ISCA Code of Ethics, pre-prints policy and conference policy read 2. At most 6 pages (regular) or 10 (long paper); last pages only for acknowledgements, AI disclosure and references 3. Fully anonymized, including PDF metadata, self-citations and supplementary repositories 4. Generative AI used only for editing and polishing, reported in the dedicated section 5. Scientific reporting checklist answered in the submission form ## LLM policy No Interspeech reviewer LLM rule was found. The ISCA Code of Ethics allows authors to use generative AI only for editing and polishing, with disclosure; treat submissions as confidential and do not upload them to LLMs. Official policy: https://interspeech2026.org/en-AU --- Simulate reviews of your own draft in this venue's form: https://reviewpaper.ai/new?venue=interspeech (3 free reviews). Sample report: https://reviewpaper.ai/sample. reviewpaper.ai is for authors checking their own unpublished drafts. If you are an assigned reviewer, follow your venue's LLM policy: most venues forbid putting a submission you are reviewing into any external AI tool. Not affiliated with any conference.