Customer-obsessed science

Reducing the Annualized Replacement Rate (ARR) of a product brings a two-fold benefit to its sustainability impact. Firstly, it reduces the warranty stockpile and therefore a lower carbon footprint required to fulfill warranty replacements. Secondly, it extends the lifetime of the product, which reduces the overall carbon footprint every year during use. This paper discusses a methodology to quantify the

Identification of the language of performance of songs is important for applications such as personalized recommendations, discovery, and search. In this paper, we present an automated multimodal approach to identify the singing language of songs that scales to millions of songs. The proposed model uses a variety of song-level features, including a consumption embedding derived from sessions listening data

We review current solutions and technical challenges for automatic speech recognition, keyword spotting, device arbitration, speech enhancement, and source localization in multi-device home environments to provide context for the INTERSPEECH 2022 special session, “Challenges and opportunities for signal processing and machine learning for multiple smart devices”. We also identify the datasets needed to

Bayesian optimization (BO) is a widely popular approach for the hyperparameter optimization (HPO) in machine learning. At its core, BO iteratively evaluates promising configurations until a user-defined budget, such as wall-clock time or number of iterations, is exhausted. While the final performance after tuning heavily depends on the provided budget, it is hard to pre-specify an optimal value in advance

In this paper, we present CopyCat2 (CC2), a novel model capable of: a) synthesizing speech with different speaker identities, b) generating speech with expressive and contextually appropriate prosody, and c) transferring prosody at fine-grained level between any pair of seen speakers. We do this by activating distinct parts of the network for different tasks. We train our model using a novel approach to