June 26, 2024 - With this model, the researchers were able to generate representations of the acoustic data collected from the dogs and interpret these representations. They found that Wav2Vec2 not only succeeded at four classification tasks; it also outperformed other models trained specifically on dog bark data, with accuracy figures up to 70%.

April 29, 2024 - To create acoustic representations of the dog vocalizations in the dataset, we fine-tune a pre-trained state-of-the-art self-supervised speech representation model. We use Wav2Vec2 Baevski et al. (2020), which uses a self-supervised training objective to predict masked latent representations, ...

June 10, 2024 - In a groundbreaking study, researchers ... interpret dog barks. By modifying the Wav2Vec2 machine-learning model, initially designed for human speech, they successfully interpreted the acoustic data from dogs....

June 6, 2024 - To tackle this challenge, the researchers turned to a dataset of dog vocalizations recorded from 74 dogs of various breeds, ages, and sexes in diverse contexts. By adapting an existing machine-learning model called Wav2Vec2, originally trained on human speech, they were able to successfully ...

Below is an expected speedup diagram comparing the pure inference time between the native implementation in transformers of the facebook/wav2vec2-large-960h-lv60-self model and the flash-attention-2 and sdpa (scale-dot-product-attention) versions.

In this notebook, we will give an in-detail explanation of how Wav2Vec2's pretrained checkpoints can be fine-tuned on any English ASR dataset. Note that in this notebook, we will fine-tune Wav2Vec2 without making use of a language model. It is much simpler to use Wav2Vec2 without a language model as an end-to-end ASR system and it has been shown that a standalone Wav2Vec2 acoustic model achieves impressive results.

Wav2Vec2 model to dog identification.

June 10, 2024 - The model was able to generate and interpret acoustic data from the dog noises to determine how the animal was feeling. The bark-infused Wav2Vec2 model was 70% accurate in determining the dog’s mood, as well as its breed, age and sex, outperforming other models trained on related data.

June 5, 2024 - Using one of these models, Wav2Vec2, they used vocalizations from 74 dogs of various breeds, sex, and ages to train the AI to analyze the tones of different dog sounds.

With this model, the researchers were able to generate representations of the acoustic data collected from the dogs and interpret these representations. They found that Wav2Vec2 not only succeeded at four classification tasks; it also outperformed other models trained specifically on dog bark data, with accuracy figures up to 70%.

The AI model, known as Wav2Vec2, was trained on two different datasets: one consisting entirely of dog barks and another pre-trained on nearly 1,000 hours of human speech and then fine-tuned on dog barks.

June 11, 2024 - From these recordings, the study ... barking at a stranger.” An AI model called Wav2Vec2 - which was originally designed for human speech recognition - was then trained on these hound sounds before being put through its paces ...

2 weeks ago - With this model, the researchers were able to generate representations of the acoustic data collected from the dogs and interpret these representations. They found that Wav2Vec2 not only succeeded at four classification tasks; it also outperformed other models trained specifically on dog bark data, with accuracy figures up to 70%.

June 7, 2024 - In this study, the researchers focused on identifying specific emotions in dog barks, such as aggression, normalcy, negative squeals, and negative grunts. The AI model, known as Wav2Vec2, was trained on two different datasets: one consisting entirely of dog barks and another pre-trained on ...

June 12, 2024 - This included recording the sounds made during play and affection with the owner, the noises made upon the introduction of a stranger, or the dog’s reaction to the repeated ringing of a doorbell. This data was then fed into a machine learning model created to study human speech patterns called Wav2Vec2.

June 11, 2024 - The researchers used pre-established speech recognition engines like Wav2Vec2, managing to improve the accuracy of tasks such as dog recognition, breed identification, gender classification, and context grounding.

You can use any wav2vec2 model from the huggingface model hub.

The Wav2Vec2 model was modified to interpret dog vocalizations using a dataset recorded from 74 dogs of various breeds, ages, and sexes.