Muvox LLC v. Netaktion LLC

I. Executive Summary and Procedural Information

• Parties & Counsel:
  • Plaintiff: Muvox LLC (New Mexico)
  • Defendant: Netaktion LLC (New York)
  • Plaintiff’s Counsel: Rabicoff Law LLC
• Case Identification: 1:24-cv-09137, S.D.N.Y., 11/27/2024
• Venue Allegations: Venue is asserted based on Defendant having an established place of business in the Southern District of New York and having committed alleged acts of patent infringement within the district.
• Core Dispute: Plaintiff alleges that Defendant’s unspecified music products and services infringe a patent related to a system for categorizing music tracks using computer-derived acoustic scores to generate playlists.
• Technical Context: The technology at issue concerns the automated analysis of audio files to classify music by mood or other characteristics, a central feature in the competitive digital music streaming and playlist curation market.
• Key Procedural History: The complaint does not reference any prior litigation involving the patent-in-suit, any post-grant proceedings before the U.S. Patent and Trademark Office, or any known licensing history.

Case Timeline

II. Technology and Patent(s)-in-Suit Analysis

U.S. Patent No. 11,899,713 - "Music streaming, playlist creation and streaming architecture"

• Patent Identification: U.S. Patent No. 11,899,713, “Music streaming, playlist creation and streaming architecture,” issued February 13, 2024.

The Invention Explained

• Problem Addressed: The patent’s background section describes a market challenge for music publishing entities (such as radio stations or independent record labels) that own music catalogs but lack a practical method to offer sophisticated, mood-based streaming services to end-users in the manner of major platforms like Spotify or Apple Music (’713 Patent, col. 1:41-59).
• The Patented Solution: The invention proposes a system that automatically analyzes music tracks to generate objective "Rhythm, Texture, and Pitch (RTP)" scores, which correspond to musical moods (’713 Patent, col. 2:5-16). These scores are stored in a "universal database" shared among multiple music publishers, obviating the need to re-analyze the same track multiple times (’713 Patent, col. 2:17-23). An end-user application, sponsored by a single publisher, accesses this database via an API to create personalized playlists, while the music itself is streamed exclusively from the sponsoring publisher's library, as depicted in the system architecture of Figure 2 (’713 Patent, col. 2:25-33; Fig. 2).
• Technical Importance: The described architecture is presented as a way to enable a broader range of content owners to provide advanced playlist-curation features without the cost and complexity of building and licensing a comprehensive, standalone streaming service (’713 Patent, col. 1:59-67).

Key Claims at a Glance

• The complaint asserts infringement of one or more unspecified claims of the ’713 Patent (Compl. ¶11). The patent’s independent claims are 1 (a method) and 16 (a system).
• Independent Claim 1 (Method): The essential elements include:
  • Selecting a song based on a "computer-derived comparison" between a "representation of the song" and known similarities in representations of other songs.
  • The known similarities are based on a "human-trained machine".
  • The song's representation is based on its "frequency characteristics".
  • The machine is trained using representations of other songs, which are based on "human listening" to identify frequency characteristics corresponding to "one or more moods".
  • The selection is based on the "similarity" between the moods of the song and the moods of the other songs.
• Independent Claim 16 (System): The essential elements include:
  • Sampling "frequency data" from a song and generating a "representation" of it.
  • Filtering the representation to create a "digitized representation" that corresponds to one or more "attributes" of the song.
  • Comparing this digitized representation to known similarities from other songs, where the similarities are derived from a "human-trained machine" based on "human listening" to identify "frequency characteristics" corresponding to "moods".
  • Selecting the song based on the "one or more similar moods".
• The complaint reserves the right to assert infringement of other claims, including dependent claims (Compl. ¶11).

III. The Accused Instrumentality

Product Identification

The complaint does not identify any specific accused products, methods, or services by name, referring to them generally as “Exemplary Defendant Products” and “Defendant products” (Compl. ¶¶11, 14).

Functionality and Market Context

The complaint alleges that the accused products "practice the technology claimed by the '713 Patent" but does not provide any specific technical details regarding their operation or features (Compl. ¶16). All detailed infringement allegations are incorporated by reference from an "Exhibit 2" that was not filed with the complaint (Compl. ¶17). As a result, the complaint does not provide sufficient detail for analysis of the accused instrumentality's functionality or market context.

IV. Analysis of Infringement Allegations

The complaint references, but does not include, "Exhibit 2," which purportedly contains claim charts comparing the asserted claims to the accused products (Compl. ¶¶16-17). In the absence of this exhibit, a detailed claim chart summary cannot be constructed. The complaint’s narrative infringement theory is that the "Exemplary Defendant Products... satisfy all elements of the Exemplary '713 Patent Claims" (Compl. ¶16).

No probative visual evidence provided in complaint.

• Identified Points of Contention: Based on the patent’s claims and the general nature of the allegations, the infringement analysis raises several key questions:
  • Scope Questions: The claims require a "human-trained machine" whose training is based on "human listening" to establish mood correlations. A central question may be whether Defendant's system, if it uses a machine learning model, was trained in the specific manner required by the claims, or if it was trained on other data (e.g., user activity, genre labels), which may support a non-infringement defense.
  • Technical Questions: What evidence does Plaintiff possess to allege that Defendant's products select music based on a comparison of "moods" derived from "frequency characteristics"? The case may turn on whether the accused system's song-selection algorithm functions as claimed, or if it relies on alternative methods like collaborative filtering, artist similarity, or other metadata not covered by the patent.

V. Key Claim Terms for Construction

• The Term: "human-trained machine" (Claim 1, 16)

• Context and Importance: This term is foundational to the claimed invention, defining the specific type of analytical engine at the system's core. Practitioners may focus on this term because the outcome of the case could depend on whether the accused system's artificial intelligence or machine learning component falls within this definition.

• Intrinsic Evidence for Interpretation:

  • Evidence for a Broader Interpretation: The specification discusses the use of a "neural network" and techniques like "audio data augmentation," which are common in modern machine learning, potentially supporting a construction that covers a range of AI systems (’713 Patent, col. 5:58-6:11).
  • Evidence for a Narrower Interpretation: The claims explicitly link the machine's training to an initial phase of "human listening to each of the plurality of the other songs" to isolate frequency characteristics corresponding to moods (’713 Patent, col. 25:36-41; col. 26:5-10). This language may support a narrower construction requiring a specific, human-supervised training pipeline rather than any generic, pre-trained model.

• The Term: "frequency characteristics" (Claim 1)

• Context and Importance: This term defines the raw technical data that the system must use to perform its mood analysis. The infringement determination will depend on whether the data inputs for the accused system's algorithm qualify as "frequency characteristics" as understood in the patent.

• Intrinsic Evidence for Interpretation:

  • Evidence for a Broader Interpretation: The patent describes the inputs in general terms, such as "frequency-related data (i.e., frequencies, structure and organization)," which could suggest the term covers any analysis within the frequency domain of an audio signal (’713 Patent, col. 3:24-26).
  • Evidence for a Narrower Interpretation: The specification provides a list of concrete examples of low-level data, including "spectrograms," "chromagrams," "mel-spectrograms," "Beats per minute histogram," and "Mel-frequency cepstral coefficients (MFCCs)" (’713 Patent, col. 4:39-47; col. 5:7-25). This specificity may be used to argue that the term is limited to these or technically similar forms of audio analysis.

VI. Other Allegations

• Indirect Infringement: The complaint alleges induced infringement, stating that Defendant distributes "product literature and website materials" that instruct and encourage end users to use the accused products in a manner that directly infringes the ’713 Patent (Compl. ¶14).
• Willful Infringement: The complaint does not allege pre-suit knowledge of the patent. Instead, it asserts that the filing of the complaint itself provides "actual knowledge," which may form the basis for a claim of post-filing willful infringement (Compl. ¶13).

VII. Analyst’s Conclusion: Key Questions for the Case

1. A core issue will be one of technical implementation: Can Plaintiff prove that the accused system employs a "human-trained machine" consistent with the patent's specific description—a process grounded in initial "human listening" to establish mood correlations—or does the system use a more generic machine learning model that falls outside the claim scope?
2. A second central question will be one of evidentiary proof: What evidence will emerge to show that the accused products' song selection mechanism is driven by an analysis of "frequency characteristics" to determine "mood", as claimed, versus alternative, non-infringing methods such as user-based collaborative filtering, genre-tagging, or other forms of metadata analysis?
3. Given the complaint’s failure to name the accused products and its reliance on an unprovided exhibit for all substantive infringement details, a threshold issue may be the sufficiency of the pleadings. The court may first need to address whether the allegations, as filed, meet the plausibility standard required to proceed with discovery.