Voice Cloning

Copyright cannot be claimed in a voice. Copyright law protects only expression, not a person’s corporeal attributes.

Nipper, painting of dog listening to phonograph, by Francis Barraud (1898-1899)
Painting of Nipper by Francis Barraud (1898-99); subsequently used as a trademark with “His Master’s Voice.”

 

Voice cloning is one of the generative-AI technologies that I have described as a perfect tool for the age of deception. Now the issues it raises are reaching the courts. 

Lehrman v. Lovo, Inc.

On July 10, 2025, the federal district court for the Southern District of New York issued an Order granting in part and denying in part a motion to dismiss a putative class action lawsuit that Paul Lehrman and Linnea Sage commenced against Lovo, Inc. The lawsuit, Lehrman v. Lovo, Inc., alleges that Lovo used artificial intelligence to make and sell unauthorized “clones” of their voices.

Specifically, the complaint alleges that the plaintiffs are voice-over actors. For a fee, they read and record scripts for their clients. Lovo allegedly sells a text-to-speech subscription service that allows clients to generate voice-over narrations. The service is described as one that uses “AI-driven software known as ‘Generator’ or ‘Genny,'” which was “created using ‘1000s of voices.'” Genny allegedly creates voice clones, i.e., copies of real people’s voices. Lovo allegedly granted its customers “commercial rights for all content generated,” including “any monetized, business-related uses such as videos, audio books, advertising promotion, web page vlogging, or product integration.” (Lovo terms of service.) The complaint alleges that Lovo hired the plaintiffs to provide voice recordings for “research purposes only,” but that Lovo proceeded to exploit them commercially by licensing their use to Lovo subscribers.

This lawsuit ensued.

The complaint sets out claims for:

  • Copyright infringement
  • Trademark infringement
  • Breach of contract
  • Fraud
  • Conversion
  • Unjust enrichment
  • Unfair competition
  • New York civil rights laws
  • New York consumer protection laws.

The defendant moved to dismiss the complaint for failure to state a claim.

The copyright claims

Sage alleged that Lovo infringed the copyright in one of her voice recordings by reproducing it in presentations and YouTube videos. The court allowed this claim to proceed.

Plaintiffs also claimed that Lovo’s unauthorized use of their voice recordings in training its generative-AI product infringed their copyrights in the sound recordings. The court ruled that the complaint did not contain enough factual detail about how the training process infringed one of the exclusive rights of copyright ownership. Therefore, it dismissed this claim with leave to amend.

The court dismissed the plaintiffs’ claims of output infringement, i.e., claims that the “cloned” voices the AI tool generated infringed copyrights in the original sound recordings.

Copyright protection in a sound recording extends only to the actual recording itself. Fixation of sounds that imitate or simulate the ones captured in the original recording does not infringe the copyright in the sound recording.

This issue often comes up in connection with copyrights in music recordings. If Chuck Berry writes a song called “Johnny B. Goode” and records himself performing it, he will own two copyrights – one in the musical composition and one in the sound recording. If a second person then records himself performing the same song, and he doesn’t have a license (compulsory or otherwise) to do so, that person would be infringing the copyright in the music but not the copyright in the sound recording. This is true even if he is very good at imitating Berry’s voice and guitar work. For a claim of sound recording infringement to succeed, it must be shown that the actual recording itself was copied.

Plaintiffs did not allege that Lovo used Genny to output AI-generated reproductions of their original recordings. Rather, they alleged that Genny is able to create new recordings that mimic attributes of their voices.

The court added that the sound of a voice is not copyrightable expression, and even if it were, the plaintiffs had registered claims of copyright in their recordings, not in their voices.

The trademark claims

In addition to infringement, the Lanham Act creates two other potential bases of trademark liability: (1) false association; and (2) false advertising. 15 U.S.C. sec. 1125(a)(1)(A) and (B). Plaintiffs asserted both kinds of claims. The judge dismissed these claims.

False association

The Second Circuit court of appeals recently held, in Electra v. 59 Murray Enter., Inc. and Souza v. Exotic Island Enters., Inc., that using a person’s likeness to create an endorsement without the person’s permission can constitute a “false association” violation. In other words, a federally-protected, trademark-like interest in one’s image, likeness, personality and identity exists. (See, e.g., Jackson v. Odenat.)

Although acknowledging that this right extends to one’s voice, the judge ruled that the voices in this case did not function as trademarks. They did not identify the source of a product or service. Rather, they were themselves the product or service. For this reason, the judge ruled that the plaintiffs had failed to show that their voices, as such, are protectable trademarks under Section 43(a)(1)(A) of the Lanham Act.

False Advertising

Section 43(a)(1)(B) of the Lanham Act (codified at 15 U.S.C. sec. 1125(a)(1)(B)) prohibits misrepresentations about “the nature, characteristics, qualities, or geographic origin of . . . goods, services, or commercial activities.” The plaintiffs claimed that Lovo marketed their voices under different names (“Kyle Snow” and “Sally Coleman.”) The court determined that this was not fraudulent, however, because Lovo marketed them as what they were, namely, synthetic clones of the actors’ voices, not as their actual voices.

Plaintiffs also claimed that Lovo’s marketing materials falsely stated that the cloned voices “came with all commercial rights.” They asserted that they had not granted those rights to Lovo. The court ruled, however, that even if Lovo was guilty of misrepresentation, it was not the kind of misrepresentation that comes within Section 43(a)(1)(B), as it did not concern the nature, characteristics, qualities, or geographic origin of the voices.

State law claims

Although the court dismissed the copyright and trademark claims, it allowed some state law claims to proceed. Specifically, the court denied the motion to dismiss claims for breach of contract, violations of sections 50 and 51 of the New York Civil Rights Law, and violations of New York consumer protection law.

Both the common law and the New York Civil Rights Law prohibit the commercial use of a living person’s name, likeness or voice without consent. Known as “misappropriation of personality” or violation of publicity rights, this is emerging as one of the leading issues in AI law.

The court also allowed state law claims of false advertising and deceptive trade practices to proceed. The New York laws are not subject to the “nature, characteristics, qualities, or geographic origin” limitation set out in Section 43(a) of the Lanham Act.

Conclusion

I expect this case will come to be cited for the rule that copyright cannot be claimed in a voice. Copyright law protects only expression, not a person’s corporeal attributes. The lack of copyright protection for a person’s voice, however, does not mean that voice cloning is “legal.” Depending on the particular facts and circumstances, it may violate one or more other laws.

It also should be noted that after the Joe Biden voice-cloning incident of 2024, states have been enacting statutes regulating the creation and distribution of voice clones. Even where a specific statute is not applicable, though, a broader statute (such as the FTC Act or a similar state law) might cover the situation.

Images and references in this blog post are for illustrative purposes only. No endorsement, sponsorship or affiliation with any person, organization, company, brand, product or service is intended, implied, or exists.

Joe Biden portrait
Official portrait of Vice President Joe Biden in his West Wing Office at the White House, Jan. 10, 2013. (Official White House Photo by David Lienemann)

 

Court Rules AI Training is Fair Use

Court rules that using copyrighted works to train AI is fair use. Kadrey et al. v. Meta Platforms.

Just days after the first major fair use ruling in a generative-AI case, a second court has determined that using copyrighted works to train AI is fair use. Kadrey et al. v. Meta Platforms, No. 3:23-cv-03417-VC (N.D. Cal. June 25, 2025).

The Kadrey v. Meta Platforms Lawsuit

I previously wrote about this lawsuit in an article describing the top 12 generative-AI lawsuits.

Meta Platforms owns and operates social media services including Facebook, Instagram, and WhatsApp. It is also the developer of a large language model (LLM) called “Llama.” One of its releases, Meta AI, is an AI chatbot that utilizes Llama.

To train its AI, Meta obtained data from a wide variety of sources. The company initially pursued licensing deals with book publishers. It turned out, though, that in many cases, individual authors owned the copyrights. Unlike music, no organization handles collective licensing of rights in book content. Meta then downloaded shadow library databases. Instead of licensing works in the databases, Meta decided to just go ahead and use them without securing licenses. To download them more quickly, Meta torrented them using BitTorrent.

Meta trained its AI models to prevent them from “memorizing” and outputting text from the training data, with the result that no more than 50 words and punctuation marks from any given work were reproduced in any given output.

The plaintiffs named in the Complaint are thirteen book authors who have published novels, plays, short stories, memoirs, essays, and nonfiction books. Sarah Silverman, author of The Bedwetter; Junot Diaz, author of The Brief Wondrous Life of Oscar Wao; and Andrew Sean Greer, author of Less, are among the authors named as plaintiffs in the lawsuit. The complaint alleges that Meta downloaded 666 copies of their books without permission and states claims for direct copyright infringement, vicarious copyright infringement, removal of copyright management information in violation of the Digital Millennium Copyright Act (DMCA), and various state law claims. All claims except the ones for direct copyright infringement and violation of the DMCA were dismissed in prior proceedings.

Both sides moved for summary judgment on fair use with respect to the claim that Meta’s use of the copyrighted works to train its AI infringed copyrights. Meta moved for summary judgment on the DMCA claims. Neither side moved for summary judgment on a claim that Meta infringed copyrights by distributing their works (via leeching or seeding).

On June 25, 2025 Judge Chhabria granted Meta’s motion for summary judgment on fair use with respect to AI training; reserved the motion for summary judgment on the DMCA claims for decision in a separate order, and held that the claim of infringing distribution via leeching or seeding “will remain a live issue in the case.”

Judge Chhabria’s Fair Use Analysis

Judge Chhabria analyzed each of the four fair use factors. As is the custom, he treated the first (Character or purpose of the use) and fourth (Effect on the market for the work) factors as the most important of the four.

He disposed of the first factor fairly easily, as Judge Alsup did in Bartz v. Anthropic, finding that the use of copyrighted works to train AI is a transformative use. This finding weighs heavily in favor of fair use. The purpose of Meta’s AI tools is not to generate books for people to read. Indeed, in this case, Meta had installed guardrails to prevent the tools from generating duplicates or near-duplicates of the books on which the AI was trained. Moreover, even if it could allow a user to prompt the creation of a book “in the style of” a specified author, there was no evidence that it could produce an identical work or a work that was substantially similar to one on which it had been trained. And writing styles are not copyrightable.

Significantly, the judge held that the use of shadow libraries to obtain unauthorized copies of books does not necessarily destroy a fair use defense. When the ultimate use to be made of a work is transformative, the downloading of books to further that use is also transformative, the judge wrote. This ruling contrasts with other judges who have intimated that using pirated copies of works weighs against, or may even prevent, a finding of fair use.

Unlike some judges, who tend to consider the fair use analysis over and done if transformative use is found, Judge Chhabria recognized that even if the purpose of the use is transformative, its effect on the market for the infringed work still has to be considered.

3 Ways of Proving Adverse Market Effect

The Order lays out three potential kinds of arguments that may be advanced to establish the adverse effect of an infringing use on the market for the work:

  1. The infringing work creates a market substitute for the work;
  2. Use of the work to train AI without permission deprives copyright owners of a market for licenses to use their works in AI training;
  3. Dilution of the market with competing works.

Market Substitution

In this case, direct market substitution could not be established because Meta had installed guardrails that prevented users from generating copies of works that had been used in the training. Its AI tools were incapable of generating copies of the work that could serve as substitutes for the authors’ works.

The Market for AI Licenses

The court refused to recognize the loss of potential profits from licensing the use of a work for AI training purposes as a cognizable harm.

Market Dilution

The argument here would be that the generation of many works that compete in the same market as the original work on which the AI was trained dilutes the market for the original work. Judge Chhabria described this as indirect market substitution.

The copyright owners in this case, however, focused on the first two arguments. They did not present evidence that Meta’a AI tools were capable of generating books; that they do, in fact, generate books; or that the books they generate or are capable of generating compete with books these authors wrote. There was no evidence of diminished sales of their books.

Market harm cannot be assumed when generated copies are not copies that can serve as substitutes for the specific books claimed to have been infringed. When the output is transformative, as it was in this case, market substitution is not self-evident.

Judge Chhabria chided the plaintiffs for making only a “half-hearted argument” of a significant threat of market harm. He wrote that they presented “no meaningful evidence on market dilution at all.”

Consequently, he ruled that the fourth fair use factor favored Meta.

Conclusion

The decision in this case is as significant for what the court didn’t do as it is for what it did. It handed a fair use victory to Meta. At the same time, though, it did not rule out a finding that training AI tools on copyrighted works is not fair use in an appropriate case. The court left open the possibility that a copyright owner might prevail on a claim that training AI on copyrighted works is not fair use in a different case. And it pointed the way, albeit in dictum, namely, by making a strong showing of market dilution.

That claim is not far-fetched. https://www.wired.com/story/scammy-ai-generated-books-flooding-amazon/

AI OK; Piracy Not: Bartz v. Anthropic

Anthropic also acquired infringing copies of works from pirate sites. Judge Alsup ruled that these, and uses made from them, are not fair use.

A federal judge has issued a landmark fair use decision in a generative-AI copyright infringement lawsuit.

In a previous blog post, I wrote about the fair use decision in Thomson Reuters v. ROSS. As I explained there, that case involved a search-and-retrieval AI system, so the holding was not determinative of fair use in the context of generative AI. Now we finally have a decision that addresses fair use in the generative-AI context.

Bartz et al. v. Anthropic PBC

I did not include this case in my list of the top 12 generative-AI lawsuits, but only because it was one among many raising the same basic questions about training AI on copyright-protected works. This issue was well represented by others on the list. As it happens, though, Bartz has now taken on enhanced significance because the judge in the case has issued an important ruling on fair use.

Anthropic is an AI software firm founded by former OpenAI employees. It offers a generative-AI tool called Claude. Like other generative-AI tools, Claude mimics human conversational skills. When a user enters a text prompt, Claude will generate a response that is very much like one a human being might make (except it is sometimes more knowledgeable.) It is able to do this by using large language models (LLMs) that have been trained on millions of books and texts.

Adrea Bartz, Charles Graeber, and Kirk Wallace Johnson are book authors. In August 2024, they sued Anthropic, claiming the company infringed the copyrights in their works. Specifically, they alleged that Anthropic copied their works from pirated and purchased sources, digitized print versions, assembled them into a central library, and used the library to train LLMs, all without permission. Anthropic asserted, among other things, a fair use defense.

Earlier this year, Anthropic filed a motion for summary judgment on the question of fair use.

On June 23, 2025, Judge Alsup issued an Order granting summary judgment in part and denying it in part. It is the first major ruling on fair use in the dozens of generative-AI copyright infringement lawsuits that are currently pending in federal courts.

The Order includes several key rulings.

Books

Digitization

Anthropic acquired both pirated and lawfully purchased printed copies of copyright-protected works and digitized them to create a central e-library. Authors claimed that making digital copies of their works infringed the exclusive right of copyright owners to reproduce their works. (See 17 U.S.C. 106.)

In the process of scanning print books to create digital versions of them, the print copies were destroyed. Book bindings were stripped so that each individual page could be scanned. The print copies were then discarded. The digital copies were not distributed to others. Under these circumstances, the court ruled that making digital versions of print books is fair use.

The court likened format to a frame around a work, as distinguished from the work itself. As such, a digital version is not a new derivative work. Rather, it is a transformative use of an existing work. So long as the digital version is merely a substitute for a print version a person has lawfully acquired, and so long as the print version is destroyed and the digital version is not further copied or distributed to others, then digitizing a printed work is fair use. This is consistent with the first sale doctrine (17 U.S.C. 109(a)), which gives the purchaser of a copy of a work a right to dispose of that particular copy as the purchaser sees fit.

In short, the mere conversion of a lawfully acquired print book to a digital file to save space and enable searchability is transformative, and so long as the print version is destroyed and the digital version is not further copied or distributed, it is fair use.

AI Training Is Transformative Fair Use

The authors did not contend that Claude generated infringing output. Instead, they argued that copies of their works were used as inputs to train the AI. The Copyright Act, however, does not prohibit or restrict the reading or analysis of copyrighted works. So long as a copy is lawfully purchased, the owner of the purchased copy can read it and think about it as often as he or she wishes.

[I]f someone were to read all the modern-day classics because of their exceptional expression, memorize them, and then emulate a blend of their best writing, would that violate the Copyright Act? Of course not.

Order.

Judge Alsup described AI training as “spectacularly” transformative.” Id. After considering all four fair use factors, he concluded that training AI on lawfully acquired copyright-protected works (as distinguished from the initial acquisition of copies) is fair use.

Pirating Is Not Fair Use

In addition to lawfully purchasing copies of some works, Anthropic also acquired infringing copies of works from pirate sites. Judge Alsup ruled that these, and uses made from them, are not fair use. The case will now proceed to trial on the issue of damages resulting from the infringement.

Conclusion

Each of these rulings seems, well, sort of obvious. It is nice to have the explanations laid out so clearly in one place, though.