| | --- |
| | annotations_creators: |
| | - expert-generated |
| | language_creators: |
| | - found |
| | language: |
| | - en |
| | license: |
| | - unlicense |
| | multilinguality: |
| | - monolingual |
| | paperswithcode_id: ljspeech |
| | pretty_name: LJ Speech |
| | size_categories: |
| | - 10K<n<100K |
| | source_datasets: |
| | - original |
| | task_categories: |
| | - automatic-speech-recognition |
| | - text-to-speech |
| | - text-to-audio |
| | task_ids: [] |
| | train-eval-index: |
| | - config: main |
| | task: automatic-speech-recognition |
| | task_id: speech_recognition |
| | splits: |
| | train_split: train |
| | col_mapping: |
| | file: path |
| | text: text |
| | metrics: |
| | - type: wer |
| | name: WER |
| | - type: cer |
| | name: CER |
| | dataset_info: |
| | features: |
| | - name: id |
| | dtype: string |
| | - name: audio |
| | dtype: |
| | audio: |
| | sampling_rate: 22050 |
| | - name: file |
| | dtype: string |
| | - name: text |
| | dtype: string |
| | - name: normalized_text |
| | dtype: string |
| | config_name: main |
| | splits: |
| | - name: train |
| | num_bytes: 4667022 |
| | num_examples: 13100 |
| | download_size: 2748572632 |
| | dataset_size: 4667022 |
| | --- |
| | |
| | # Dataset Card for lj_speech |
| | |
| | ## Table of Contents |
| | - [Dataset Description](#dataset-description) |
| | - [Dataset Summary](#dataset-summary) |
| | - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
| | - [Languages](#languages) |
| | - [Dataset Structure](#dataset-structure) |
| | - [Data Instances](#data-instances) |
| | - [Data Fields](#data-fields) |
| | - [Data Splits](#data-splits) |
| | - [Dataset Creation](#dataset-creation) |
| | - [Curation Rationale](#curation-rationale) |
| | - [Source Data](#source-data) |
| | - [Annotations](#annotations) |
| | - [Personal and Sensitive Information](#personal-and-sensitive-information) |
| | - [Considerations for Using the Data](#considerations-for-using-the-data) |
| | - [Social Impact of Dataset](#social-impact-of-dataset) |
| | - [Discussion of Biases](#discussion-of-biases) |
| | - [Other Known Limitations](#other-known-limitations) |
| | - [Additional Information](#additional-information) |
| | - [Dataset Curators](#dataset-curators) |
| | - [Licensing Information](#licensing-information) |
| | - [Citation Information](#citation-information) |
| | - [Contributions](#contributions) |
| | |
| | ## Dataset Description |
| | |
| | - **Homepage:** [The LJ Speech Dataset](https://keithito.com/LJ-Speech-Dataset/) |
| | - **Repository:** [N/A] |
| | - **Paper:** [N/A] |
| | - **Leaderboard:** [Paperswithcode Leaderboard](https://paperswithcode.com/sota/text-to-speech-synthesis-on-ljspeech) |
| | - **Point of Contact:** [Keith Ito](mailto:kito@kito.us) |
| | |
| | ### Dataset Summary |
| | |
| | This is a public domain speech dataset consisting of 13,100 short audio clips of a single speaker reading passages from 7 non-fiction books in English. A transcription is provided for each clip. Clips vary in length from 1 to 10 seconds and have a total length of approximately 24 hours. |
| | |
| | The texts were published between 1884 and 1964, and are in the public domain. The audio was recorded in 2016-17 by the LibriVox project and is also in the public domain. |
| | |
| | ### Supported Tasks and Leaderboards |
| | |
| | The dataset can be used to train a model for Automatic Speech Recognition (ASR) or Text-to-Speech (TTS). |
| | - `automatic-speech-recognition`: An ASR model is presented with an audio file and asked to transcribe the audio file to written text. |
| | The most common ASR evaluation metric is the word error rate (WER). |
| | - `text-to-speech`, `text-to-audio`: A TTS model is given a written text in natural language and asked to generate a speech audio file. |
| | A reasonable evaluation metric is the mean opinion score (MOS) of audio quality. |
| | The dataset has an active leaderboard which can be found at https://paperswithcode.com/sota/text-to-speech-synthesis-on-ljspeech |
| | |
| | ### Languages |
| | |
| | The transcriptions and audio are in English. |
| | |
| | ## Dataset Structure |
| | |
| | ### Data Instances |
| | |
| | A data point comprises the path to the audio file, called `file` and its transcription, called `text`. |
| | A normalized version of the text is also provided. |
| | |
| | ``` |
| | { |
| | 'id': 'LJ002-0026', |
| | 'file': '/datasets/downloads/extracted/05bfe561f096e4c52667e3639af495226afe4e5d08763f2d76d069e7a453c543/LJSpeech-1.1/wavs/LJ002-0026.wav', |
| | 'audio': {'path': '/datasets/downloads/extracted/05bfe561f096e4c52667e3639af495226afe4e5d08763f2d76d069e7a453c543/LJSpeech-1.1/wavs/LJ002-0026.wav', |
| | 'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, |
| | 0.00091553, 0.00085449], dtype=float32), |
| | 'sampling_rate': 22050}, |
| | 'text': 'in the three years between 1813 and 1816,' |
| | 'normalized_text': 'in the three years between eighteen thirteen and eighteen sixteen,', |
| | } |
| | ``` |
| | |
| | Each audio file is a single-channel 16-bit PCM WAV with a sample rate of 22050 Hz. |
| |
|
| | ### Data Fields |
| |
|
| | - id: unique id of the data sample. |
| |
|
| | - file: a path to the downloaded audio file in .wav format. |
| |
|
| | - audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`. |
| |
|
| | - text: the transcription of the audio file. |
| |
|
| | - normalized_text: the transcription with numbers, ordinals, and monetary units expanded into full words. |
| | |
| | ### Data Splits |
| | |
| | The dataset is not pre-split. Some statistics: |
| | |
| | - Total Clips: 13,100 |
| | - Total Words: 225,715 |
| | - Total Characters: 1,308,678 |
| | - Total Duration: 23:55:17 |
| | - Mean Clip Duration: 6.57 sec |
| | - Min Clip Duration: 1.11 sec |
| | - Max Clip Duration: 10.10 sec |
| | - Mean Words per Clip: 17.23 |
| | - Distinct Words: 13,821 |
| | |
| | ## Dataset Creation |
| | |
| | ### Curation Rationale |
| | |
| | [Needs More Information] |
| | |
| | ### Source Data |
| | |
| | #### Initial Data Collection and Normalization |
| | |
| | This dataset consists of excerpts from the following works: |
| | |
| | - Morris, William, et al. Arts and Crafts Essays. 1893. |
| | - Griffiths, Arthur. The Chronicles of Newgate, Vol. 2. 1884. |
| | - Roosevelt, Franklin D. The Fireside Chats of Franklin Delano Roosevelt. 1933-42. |
| | - Harland, Marion. Marion Harland's Cookery for Beginners. 1893. |
| | - Rolt-Wheeler, Francis. The Science - History of the Universe, Vol. 5: Biology. 1910. |
| | - Banks, Edgar J. The Seven Wonders of the Ancient World. 1916. |
| | - President's Commission on the Assassination of President Kennedy. Report of the President's Commission on the Assassination of President Kennedy. 1964. |
| | |
| | Some details about normalization: |
| | - The normalized transcription has the numbers, ordinals, and monetary units expanded into full words (UTF-8) |
| | - 19 of the transcriptions contain non-ASCII characters (for example, LJ016-0257 contains "raison d'être"). |
| | - The following abbreviations appear in the text. They may be expanded as follows: |
| | |
| | | Abbreviation | Expansion | |
| | |--------------|-----------| |
| | | Mr. | Mister | |
| | | Mrs. | Misess (*) | |
| | | Dr. | Doctor | |
| | | No. | Number | |
| | | St. | Saint | |
| | | Co. | Company | |
| | | Jr. | Junior | |
| | | Maj. | Major | |
| | | Gen. | General | |
| | | Drs. | Doctors | |
| | | Rev. | Reverend | |
| | | Lt. | Lieutenant | |
| | | Hon. | Honorable | |
| | | Sgt. | Sergeant | |
| | | Capt. | Captain | |
| | | Esq. | Esquire | |
| | | Ltd. | Limited | |
| | | Col. | Colonel | |
| | | Ft. | Fort | |
| | (*) there's no standard expansion for "Mrs." |
| | |
| | #### Who are the source language producers? |
| | |
| | [Needs More Information] |
| | |
| | ### Annotations |
| | |
| | #### Annotation process |
| | |
| | - The audio clips range in length from approximately 1 second to 10 seconds. They were segmented automatically based on silences in the recording. Clip boundaries generally align with sentence or clause boundaries, but not always. |
| | - The text was matched to the audio manually, and a QA pass was done to ensure that the text accurately matched the words spoken in the audio. |
| | |
| | #### Who are the annotators? |
| | |
| | Recordings by Linda Johnson from LibriVox. Alignment and annotation by Keith Ito. |
| | |
| | ### Personal and Sensitive Information |
| | |
| | The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in this dataset. |
| | |
| | ## Considerations for Using the Data |
| | |
| | ### Social Impact of Dataset |
| | |
| | [Needs More Information] |
| | |
| | ### Discussion of Biases |
| | |
| | [Needs More Information] |
| | |
| | ### Other Known Limitations |
| | |
| | - The original LibriVox recordings were distributed as 128 kbps MP3 files. As a result, they may contain artifacts introduced by the MP3 encoding. |
| | |
| | ## Additional Information |
| | |
| | ### Dataset Curators |
| | |
| | The dataset was initially created by Keith Ito and Linda Johnson. |
| | |
| | ### Licensing Information |
| | |
| | Public Domain ([LibriVox](https://librivox.org/pages/public-domain/)) |
| | |
| | ### Citation Information |
| | |
| | ``` |
| | @misc{ljspeech17, |
| | author = {Keith Ito and Linda Johnson}, |
| | title = {The LJ Speech Dataset}, |
| | howpublished = {\url{https://keithito.com/LJ-Speech-Dataset/}}, |
| | year = 2017 |
| | } |
| | ``` |
| | |
| | ### Contributions |
| | |
| | Thanks to [@anton-l](https://github.com/anton-l) for adding this dataset. |
