Configuration errors
Configuration errors indicate that something about the API call was not configured correctly. The error message you get from the Hume APIs will often contain more information than we’re able to provide on this page. For example if an audio file is too long, the error message from the API will specify the limit as well as the length of the audio received.
| Error Code | Description |
|---|---|
| E0100 | The WebSocket request could not be parsed as valid JSON. The Hume API requires JSON serializable payloads. |
| E0101 | You may be missing or improperly formatting a required field. This generic error indicates that the structure of your WebSocket request was invalid. Please see the error message you received in the API response for more details. |
| E0102 | The requested model was incompatible with the file format received. Some models are not compatible with every file type. For example, no facial expressions will be detected in a text file. Audio can be extracted out of some video files, but if the video has no audio, then models like Speech Prosody and Vocal Burst will not be available. |
| E0200 | Media provided could not be parsed into a known file format. Hume APIs support a wide range of file formats and media types including audio, video, image, text, but not all formats are supported. If you receive this error and believe your file type should be supported please reach out to our support team. |
| E0201 | Media could not be decoded as a Base64 encoded string. The data field in the request payload should be Base64 encoded bytes. If you want to pass raw text without encoding it you can do so with the raw_text parameter. |
| E0202 | No audio signal could be inferred from the media provided. This error indicates that audio models were configured, but the media provided could not be parsed into a valid audio file. |
| E0203 | Your audio file was too long. The limit is 5000 milliseconds. The WebSocket endpoints are intended for near real-time processing of data streams. For larger files considering using the Hume Measurement API REST endpoints. |
| E0204 | Your video file was too long. For best performance we recommend passing individual frames of video as images rather than full video files. |
| E0205 | Your image file was too large. The limit is 3,000 x 3,000 pixels. The WebSocket endpoints are intended for near real-time processing of data streams. For larger files considering using the Hume Measurement API REST endpoints. |
| E0206 | Your text file was too long. The limit is 10,000 characters. The WebSocket endpoints are intended for near real-time processing of data streams. For larger files considering using the Hume Measurement API REST endpoints. |
| E0207 | The URL you’ve provided appears to be incorrect. Please verify that you’ve entered the correct URL and try submitting it again. If you’re copying and pasting, ensure that the entire URL has been copied without any missing characters. |
| E0300 | You’ve run out of credits. Go to beta.hume.ai to purchase more. |
| E0400 | You’ve referenced a resource that doesn’t exist in our system. Please check if the name or identifier you used is correct and try again. |
| E0401 | Your upload failed. Please ensure your file meets our format and size requirements, and attempt to upload it again. |
| E0402 | The CSV file you used to create or update a dataset is missing a header row. The header specifies what each column represents. Update your CSV file and retry your request. For more information about how to format your dataset CSV please see our tutorial on dataset creation. |
| E0500 | Your dataset doesn’t meet the minimum sample size requirement. Please add more files to your dataset and resubmit your training job. For more information, please see our docs on dataset requirements. |
| E0501 | Your dataset contains a target column with empty values. Please clean your dataset so that all labels are valid categorical or numeric values and then resubmit your training job. For more information on target columns please see our docs on dataset requirements. |
| E0502 | Your dataset contains a target column with infinite values. Please clean your dataset so that all labels are valid categorical or numeric values and then resubmit your training job. For more information on target columns please see our tutorial on dataset creation. |
| E0503 | For classification tasks, your dataset must include at least two distinct classes. Please check your dataset has two unique labels in the target column. |
| E0504 | Some classes in your dataset don’t have enough samples. To ensure that the model we produce is of the highest quality we require your dataset to be relatively balanced across classes. Please check the error message for which class should have more samples (or remove that class entirely). Please see our docs on dataset requirements for more details. |
| E0505 | The target column you’ve selected doesn’t exist in the dataset. Please review the columns that exist in your dataset and select a valid column name. |
| E0506 | Your chosen target column is not a valid target column. Please ensure that you select a column with labels rather than the file_id column or another reserved column name. |
The connection will be closed automatically after ten identical configuration errors to avoid unintended looping.
Service errors
If you encounter an error code starting with I (for example, error code I0100), it indicates an outage or a bug in a Hume service. Our team will already have been alerted of the internal error, but if you need immediate assistance please reach out to our support team.
Warnings
Warnings indicate that the payload was configured correctly, but no results could be returned.
| Error Code | Description |
|---|---|
| W0101 | No vocal bursts could be detected in the media. |
| W0102 | No face meshes could be detected in the media. |
| W0103 | No faces could be detected in the media. |
| W0104 | No emotional language could be detected in the media. |
| W0105 | No speech could be detected in the media. |
Common errors
Some errors will not have an associated error code, but are documented here.
Transcript confidence below threshold value
This error indicates that our transcription service had difficulty identifying the language spoken in your audio file or the quality was too low. We prioritize quality and accuracy, so if it cannot transcribe with confidence, our models won’t be able to process it further.
By default, we use an automated language detection method for our Speech Prosody, Language, and NER models. However, if you know what language is being spoken in your media samples, you can specify it via its BCP-47 tag and potentially obtain more accurate results.
If you see the message above there are few steps you can do to resolve the issue:
- Verify we support the language
- Ensure you are providing clear, high-quality audio files.
- Specify the language within your request if you know the language in the audio.
You can specify any of the following: zh, da, nl, en, en-AU, en-IN, en-NZ, en-GB, fr, fr-CA, de, hi, hi-Latn, id, it, ja, ko, no, pl, pt, pt-BR, pt-PT, ru, es, es-419, sv, ta, tr, or uk